In this article, a polarimetric millimeter-wave FMCW radar operating in the 222-228 GHz frequency range is proposed for mapping applications in indoor environments. Equipped with a mechanically scanning fan-beam reflector antenna with 360° field of view, the radar can generate 2D images of its scene, offering LiDAR-like azimuthal resolution of 0.3°. The system’s performance for indoor mapping as well as Line-of-Sight (LOS) and None-Line-of-Sight (NLOS) obstacle detection tasks is demonstrated in building corridors. The measurement scenarios include various wall types and wooden doors with metallic frames. The overall corridor map is created by taking multiple radar images and combining them through post-processing. Given the strong presence of ghost targets in the radar images, an algorithm is developed for NLOS target detection and localization. As a foundation for this investigation, the wave reflection coefficients of painted drywall for both vertical and horizontal polarizations, ΓVVand ΓHH, are measured. Based on these results, a novel technique for NLOS target identification using polarization discrimination is proposed and experimentally verified. This technique is further tested in a realistic scene, where an L-shaped corridor is mapped using the polarimetric radar measurement, and NLOS targets are detected and localized using a mirroring transformation.

Large scanned antenna arrays need to be periodically calibrated to correct for errors in excitation amplitude and phase, which degrade performance. The ability to adjust complex excitations to correct for these errors necessitates an accurate method to determine the errors that are present. Commonplace approaches require far-field calibration targets or sensors, additional hardware such as near-field sensors or self-sampling circuitry, or are limited to specific array configurations. These requirements are difficult to meet for arrays mounted on air- and spacecraft that cannot be easily accessed during operation or operate under transient conditions. If operating conditions change quickly, fewer types of calibrations are feasible. This could be due to temperature changes, aging and fluctuation of the electronic components, or deformation of the array structure. In [1], we show how distributed targets can be used to determine changes in element-to-element channel imbalances in pairs of receiver antennas using the underlying terrain through synthetic aperture radar (SAR) imaging. This work reports on the extension of the procedure to the calibration of an advanced wideband 16-element active electronically scanned array (AESA) with transmit and receive capabilities that we fabricated as a testbed. Several important scenarios are investigated which show that the proposed method is feasible and robust to complications present in airborne environments. These scenarios include calibration of both transmit and receive array elements, over a range of signal-to-noise ratios (SNR), and with distortions to the array structure that result in uncertainties in element positions.

Mapping the electromagnetic permittivities and thicknesses of underground layers is a vital step for proper focusing and image formation in subsurface imaging radars. Compared to traditional ground penetrating radar (GPR) that samples the scattered field along straight lines, detailed spatial information can be obtained using the concept of a newly developed subsurface multistatic synthetic aperture radar (SAR). For such system the scattered field samples are acquired along arbitrary multistatic paths. In this paper, an inversion algorithm for mapping underground layers using a multistatic subsurface SAR system is proposed. The algorithm forms a forward scattering model (FM) for the underground layers based on image theory and the generalized reflection coefficient of the layers. Subsequently, the misfit between the FM and the radar response is minimized with stochastic hill-climbing (SHC) algorithm to achieve inversion. The algorithm is tested on several full-wave simulation scenarios under noisy conditions demonstrating its potential effectiveness for mapping underground layers.

Estimating soil moisture using radar is a well-studied, but difficult application, especially when vegetation is present. A common type of agricultural vegetation is corn. Retrieving soil moisture from corn fields would be beneficial because of corn’s wide cultivation. Recent work has used full-wave scattering models to predict the radar backscatter from corn fields. A retrieval algorithm based on full-wave scattering models could have important benefits for achieving accurate results. A macromodel based on an L-band, full-wave model is developed in this work that uses second-order, multivariate polynomials to approximate the radar backscatter coefficients in terms of vegetation and soil parameters. The macromodel is used to provide an inverse model for soil moisture retrieval. The macromodel backscatter results are accurate to within ± 2 dB, and the inverse model can retrieve soil moisture to within ±2.1%.

This paper reports on polarimetric radar backscatter responses of different types of surfaces at high incidence angles (80° - 89°) at J-band frequencies (221-231 GHz). This study is motivated by the desire to understand the radar phenomenology of target scenes for the next-generation automotive radars. Measured data were collected for paved and unpaved surfaces under different conditions (dry, wet, ice- and snow-covered). At these frequencies, dry road surfaces are electrically rough and sizes of the subsurface aggregates are comparable to the signal wavelength giving rise to significant surface and volume scattering. The measured backscattering coefficients of all surfaces exhibit over 30 dB dynamic range across all data sets and significant depolarization (between -12 dB and -4 dB). For paved surfaces, the dynamic range narrows to 16 dB and the depolarization ranges between -9 dB and -4 dB. The data represent the first reported observations of radar response of surfaces at high incidence angles at J-band frequencies. They demonstrate the radar’s potential for discriminating between different types of road surfaces needed for improved safety of driverless cars. Also, based on the measured data, a semi-empirical model for the backscattering coefficients of the paved surfaces at high incidence angles is presented.

Maintaining calibration of phased array antennas in-situ is a challenging problem that is still considered open. A critical step in the array calibration process is characterizing the channel imbalances between elements so that they can be equalized. In this paper we propose a novel method for monitoring channel imbalances at elements in such arrays mounted on flying platforms using the backscatter from distributed targets within the field of view. The motion of the platform can be used to measure the backscatter of the scene in multiple positions. Synthetic aperture radar (SAR) images can be formed from these measurements using a common transmitter/receiver module and a paired receiver/transmitter module. The individual corresponding pixels of the co-registered images can be used to determine the amplitude and phase variations (channel imbalances) across the array elements. The measured phase difference between the backscatter from two co-registered images can be averaged over all pixels to provide a much better estimate of the array channel imbalances in the presence of noise. Changes in channel imbalances can be monitoredin-situwithout the need for signals-of-opportunity or strategically placed calibration targets. This could be used in the development of more elaborate array calibration algorithms, or to maintain a factory calibration during flight. The proposed method is validated under controlled conditions by forming images of a random rough surface with a two-antenna system. Average channel imbalances in amplitude and phase over frequency are recovered within a small fraction of a dB and a fraction of a degree, respectively.

Satellite and airborne radars currently monitor agricultural regions on Earth. Corn is a globally important crop that may benefit from radar observations for estimating soil moisture (SM) and other quantities. Estimates of SM could be used to enhance crop yield and aid in weather prediction. A scattering model is needed, however, to accurately estimate these quantities. Historically, corn is a difficult crop to model at microwave frequencies, and only approximate models for it exist. Novel models based on full-wave electromagnetic solvers can be more accurate by accounting for multiple scattering among plant constituents, other adjacent plants, and the underlying soil surface. Such a model is computationally expensive, but the increased availability of computing resources may make it more feasible. This article presents a model for corn at L-band based on finite element method (FEM) simulations in conjunction with Monte Carlo methods to estimate polarimetric backscattering coefficients. The FEM simulation uses periodic boundary conditions to limit its size. The physical representation of the corn plants comes from data-based 3-D plant models. The results of simulations are validated with synthetic aperture radar (SAR) data obtained during the SM active passive validation experiment of 2012 (SMAPVEX12) experimental campaign. The estimated backscattering coefficients of the SAR data are within ±2 dB for all polarization channels. Validation is performed for two days within the experimental campaign. Good agreement is observed between the simulated and measured values. This result indicates that the model can give novel insights into the scattering characteristics of corn. Future work remains to build an invertible model for estimating SM from backscatter measurements.

This paper presents a thorough phenomenological study of the responses of human subjects to millimeter-wave radars operating at J-band (220-325 GHz). In highly automated vehicles, identifying vulnerable road users such as pedestrians and bicyclist on the road and its vicinity is crucial. This paper presents various characteristics of the human body response to J-band radars and possible detection and identification techniques.

Detection and localization of buried pipelines is an important problem for oil and water distribution industries as well as for excavation and construction companies. The unique scattering mechanism exhibited by pipelines under multi-static radar configuration makes their detection and localization a challenging task. This is because the scattering phase centers (SPCs) along the pipelines change depending on the relative position between the transmitter and receiver which makes point-target based focusing algorithms such as back projection (BP) rather ineffective. To address this issue, this paper uses a special technique for determining the pipelines’ SPCs to construct a first order forward scattering model of multiple buried pipelines that considers the propagation phase and amplitude attenuation. After that, a cost function representing the misfit between the forward model and the radar response is defined. Minimization of such cost function leads to the simultaneous detection and localization of the buried pipelines. Comparison results with a basic focusing algorithm relying solely on the scattered field phase shows the superior ability of the cost function approach to resolve closely spaced buried pipelines.

Detection and localization of buried pipelines is an important problem for oil and water distribution industries as well as for excavation and construction companies. A novel 3D forward scattering model and dynamic grid search-based inversion algorithm of multiple buried pipelines using multistatic synthetic aperture radar (SAR) configuration is demonstrated in this article. Traditional imaging algorithms that focus the SAR signals by compensating only for the phase work well when the targets are far away from each other. By considering both the phase and amplitude of the scattered field and casting the inversion problem as an optimization problem, the detection and localization resolutions are improved for extended targets. A forward scattering model for multiple adjacent pipes is developed to track the scattering phase centers of each pipeline as the receiver location is changed. The model is used to calculate the resulting propagation phase and amplitude attenuation due to propagation in lossy media. The misfit between the measured data and the forward model is used as the cost function. The cost function is minimized by the dynamic grid search algorithm that starts with an initial focusing and then performs a more careful search to detect closely spaced pipelines. The forward model and inversion algorithm are validated and compared to a basic focusing algorithm using full-wave simulations as well as experimental data for both metallic as well as dielectric pipes. The results show improvement in range and cross range detection and localization resolutions over the basic SAR focusing algorithm.

A mechanically scanned high-resolution 2-D imaging radar system with full 360° Field-of-View (FoV) is presented. The system is composed of a multi-function 222-228 GHz frequency modulated continuous wave (FMCW) radar and a moment of inertia optimized 3-D printed offset reflector antenna. The reflector geometry is made from anElliptic Toroidalsurface which is shown to produce a high-gain fan-beam with an 11:1 aspect ratio. The reflector is rotated at speeds up to 10 Hz for high throughput imaging. The wobble generated by the high speed rotation is suppressed by optimizing the mass distribution of the reflector body. It is fabricated in-house using a low-cost table-top Fused Deposition Modelling (FDM) 3-D printer. The reflecting surface is metallized with a silver coated copper paint and processed using simple steps to ensure smoothness and accuracy. The reflector achieves beamwidths of 4.6° in elevation and 0.42° in azimuth, with a peak gain of 38.7 dBi. The 3 dB azimuthal resolution of the radar two-way beam is measured to be 0.3°. The system is tested in real-world scenarios and the resulting images and videos are of unprecedented quality due to the large area of coverage, high resolution, high speed and excellent dynamic range. To the best of our knowledge, this is the first demonstration of a compact radar system that is comparable in resolution, speed and angular coverage to lidars, while offering higher dynamic range and immunity to severe weather and lighting conditions.

The angular resolution of an imaging radar system is limited by the aperture size and its associated cost and complexity. Relaxing the$\lambda /2$element spacing condition for large arrays introduces sidelobe and grating lobe effects that severely degrade the image quality. In certain imaging applications, such as automotive radars, the targets are sparsely located and the imaging domain can be approximated as a collection of point scatterers. In such cases, it is possible to “deconvolve” these sidelobe effects to recover a clean image. In this article, a double-recursive deconvolution algorithm titled Sparse Array Target-Segregation Using Recursive Nulling (SATURN) is proposed. It differs from existing CLEAN deconvolution algorithms in two steps: target response estimation and multiple target decorrelation. The target response is estimated using a Sweep and Extinguish step that removes the reliance on the complex image phase. Correlation between targets is suppressed using a Recursive Nulling step that prevents the breakup of point targets. The algorithm is applied to synthetic aperture radars (SARs) and multiple-input multiple-output (MIMO) radars in sparse 3-D imaging scenarios with canonical targets and real-world targets. Dynamic range improvement of 25 dB and thinning factors of over 200 are experimentally demonstrated using a 31-element circular array of X-band U-slot patch antennas with an array diameter of$30\lambda $.

Radars operating at the higher region of the millimeter-wave frequencies are proposed to applications in new generation of automotive radars. This work is conducted to provide the base knowledge required to optimize the design and operation of such radars. Scattered signals by road surfaces provide useful information in recognizing the road condition and assessing the navigation. The radar polarimetric responses at near-grazing incidence angles of various road surfaces are characterized experimentally. Asphalt and concrete, being the most popular surfaces, are carefully measured and characterized in dry conditions. Road surface that are wet, ice-covered, or snow-covered are also examined.

A high resolution 3-D images of underground objects might be achieved using bistatic subsurface synthetic aperture radar (SAR) due the bistatic configuration's ability to view the objects from multiple angles. However, a major obstacle preventing the imaging is the dominance of the direct and ground reflection signals over the scattered signals from the buried objects. This paper presents a technique to mitigate such obstacle. By utilizing the multiple sampling points SAR provides, each adjacent sampling points are processed together as two-element array that has a null along the direction of the direct and ground reflection signals leading to significant enhancement for the scattered signals from the buried objects. The technique is explained and both simulation and measurement results for buried metallic objects are presented as a test of performance.

Monitoring corn fields with radar to measure soil moisture and biomass may yield benefits in corn cultivation. To do this, accurate forward models of corn backscatter are needed. Current models approximate the plant geometry with canonical shapes like cylinders and disks. Plant geometry and scattering may be accurately represented with 3D models and an appropriate electromagnetics solver. Using a finite-element method solver with periodic boundaries, qualitative agreement for corn backscatter is shown.

Multi-static subsurface synthetic aperture radar (SAR) is a promising tool capable of providing 3-D high resolution images of targets buried underground. The high detection capability of the system stems from the fact that the multi-static configuration allows for viewing the targets from many directions. However, a primal limiting factor for such configuration is the dominance of the direct and ground reflection signals over the scattered target signal hindering the system sensitivity. This letter presents a simple technique to overcome such drawback. By an appropriate utilization of SAR data, each adjacent sampling points are co-processed together as a two-element array in such a way as to have a null along the direction of the direct and ground reflection signals suppressing such signals and making the target signals more discernible. The technique is described in details and the potential problems arising from array processing are discussed. Additionally, a modified version of back projection imaging algorithm suitable for the array is provided. The performance of the proposed technique is assessed by simulation data of buried metallic spheres as well as measurement data for a buried metallic pipeline. Both simulation and measurements show a significant improvement in target detection and image quality.

This letter presents a new hardware setup to suppress radio frequency interference (RFI) for a recently developed microwave radiometer technique, known as wideband autocorrelation radiometry (WiBAR). WiBAR is a method that can directly measure the thickness of a low-loss layer like lake ice or dry snow on the ground by finding the lag time that corresponds to the transit time of layer in the autocorrelation function (ACF) of the received signal. However, RFI increases the noise floor of the ACF and results in a decreased signal-to-noise ratio (SNR) of the WiBAR delay peak in the ACF. We enhanced a WiBAR instrument with a tunable comb filter having a frequency response with many evenly spaced alternating pass and stop bands. We show the RFI mitigation performance of a WiBAR set-up with a comb filter in the laboratory with a simulation circuit that creates a spectrum polluted with RFI.

Subsurface pipeline detection and localization is an important problem in gas and oil transport as well as in construction and excavation missions. A 3-D subsurface multistatic imaging radar with a novel focusing algorithm for pipelines is demonstrated in this article. The traditional back-projection (BP) algorithm, which is suitable for discrete scatterers, cannot be used for extended scatterers such as pipelines whose scattering phase centers are dependent on the relative positions of the transmitter and receiver. To circumvent this problem, a new imaging algorithm that tracks the scattering phase centers in a way that is specific to pipelines is presented and shown to provide significantly better imaging performance. An analytical solution for pipeline scattering is used to derive the algorithm, and justifications for the simplifying assumptions made are provided. The algorithm is tested by applying it to realistic lossy sand simulations data as well as experimental measurements data obtained by a portable vector network analyzer (VNA). Both simulation and measurement results demonstrate the ability of the algorithm to detect and localize metallic as well as dielectric pipes.

Oil pipeline leak detection and localization is an important problem with regard to environmental issues as well as loss of resources in oil transport systems. This article shows that a 3-D subsurface multistatic imaging radar can better detect water or oil leak when more scattered signals from the leaked region are collected from multiple directions and added coherently. However, a primal drawback in achieving detection is the dominance of the signal from the pipeline itself compared to the leak signal making direct radar-based leak detection quite challenging. By utilizing the differences in the scattering mechanisms of the pipeline and the leak, this article proposes a technique that identifies and eliminates the pipeline signal from the overall radar response, which improves leak detectability. Permittivity of oil–sand mixture is determined experimentally and fit to a semiempirical mixing formula. A realistic physics-based model is used to determine the 3-D volumetric shape of oil leak. Then, the pipe with leak is simulated in a full-wave simulator with the permittivity of the leak assigned using the mixing formula. Comprehensive simulations are carried out for oil leaks in various soil mixtures and pipe materials to test the effectiveness of the proposed approach. In addition, the proposed approach is investigated experimentally using a portable vector network analyzer (VNA) where the response of a small water leak out of metallic as well as PVC pipes is measured in bistatic settings. Both simulation and measurement results demonstrate the effectiveness of the proposed approach in detecting and localizing pipeline leaks.

This article presents a comprehensive technique for calibrating wideband frequency-modulated continuous-wave (FMCW) fully polarimetric radars employing linear FM (LFM) signal chirps. A detailed system distortion model is developed that accounts for both polarimetric distortions and distortions caused by nonlinearities in the transmitted and received radar chirps over multiple polarization channels. Using the radar responses of two point targets at known distances from the radar, the calibration technique is able to estimate the range-dependent nonlinearities in phase and correct them for all targets at all ranges. This allows the radar to achieve its ideal range resolution. In addition, the calibration technique corrects for channel imbalances in the polarimetric radar using a metallic sphere of known diameter and any depolarizing target. Both numeric simulations and actual polarimetric radar measurements using a wideband FMCW radar operating over 76.5–82 GHz were used to validate the calibration technique.

In this article, a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field, is presented. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. RT equations are solved by a numerical iterative approach for both passive and active configurations. This approach allows including higher order scattering, which represents multiple scattering. In fields such as forests with large VWCs, associated with large scattering albedo and optical thickness, multiple scattering effects are critical. In the active iterative approach, cyclical terms are identified and backscattering enhancement is included by doubling contributions from cyclical terms. The method is applied to aspen trees in forest fields to compute the brightness temperatures and backscattering coefficients for passive and active remote sensing configurations, respectively. In the passive configuration, for forest field with VWC of 15 kg/$\text{m}^{2}$, the deviation between the zeroth-order brightness temperature, i.e., the tau–omega model results, and multiple scattering results around 40° observation angle, can be as large as 50 K for vertical polarization and 35 K for horizontal polarization. In the active configuration, the deviation between first-order results, which is identical to the distorted Born approximation, and the multiple scattering results around 40° incidence angle, is about 1.6 dB for VV and 0.7 dB for HH polarization. Multiple scattering is shown to be crucial for accurate forward modeling, especially over forested areas. The proposed approach is thus suitable for vegetation scattering with large VWCs. Furthermore, the proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, which demonstrates the applicability of this model.

Detecting and localizing pipeline leaks is a problem of importance as regards to environmental issues as well as loss of resources in water and oil transport systems. Since pipelines are extended targets and the oil or water leak is more localized, the methods for detection and localization of the pipeline itself and the leak are quite different. Another issue pertains to the fact that the scattered signal from the pipeline tends to be larger and can obscure the signal from the leak making direct radar-based leak detection quite challenging. To overcome this challenge, this paper proposes a technique to estimate the pipeline signal from the overall radar response then subtract it to make the oil leak signal easier to detect. The technique is explained and the simulation results for a realistic oil leak out of plastic (PVC) and metallic pipes buried in sand are reported and discussed to demonstrate the effectiveness of the technique.

Forests are an integral component of local ecosystems as well as the global carbon cycle and as a result of the subject of intense human interest and study. Synthetic Aperture Radar (SAR) and Interferometric Synthetic Aperture Radar (InSAR) are proven technologies and have both been used to image forests across weather and daylight conditions. Both SAR and InSAR systems require the formation of at least one synthetic aperture which is not an instantaneous occurrence. Rather, synthetic apertures are formed by coherently combining multiple adjacent radar observations which are collected temporally close but not simultaneously. The time required to collect sufficient measurements to form a synthetic aperture or the time between synthetic aperture collections in the case of an InSAR system are of interest in this study as both delays enable an observation of temporal processes, such as a moving wind field, and their impact on SAR and InSAR measurements. We present an approach to quantify the effect of wind on a SAR system's ability to achieve coherence between adjacent measurements and that of an InSAR system to accurately estimate the canopy height of a tree. We propose to simulate a set of physically realistic trees and to expose each to the same set of incident wind fields. During the exposure, the instantaneous geometry of each tree will be stored and then imaged by a combined SAR and InSAR simulator thereby generating a temporal record of wind-blown tree geometries and their corresponding SAR and InSAR measurements. This collection of tree geometries, wind fields, and electromagnetic simulations will be used to develop a relationship between an incident wind field and the expected impact on SAR and InSAR measurements.

This paper presents a study of snowpack thermal emissions at long wavelengths and over a wide frequency band. Brightness temperature measurements of a snow layer are reported and used to estimate the travel time through the layer. The Ultra-Wideband Software-Defined Radiometer (UWBRAD) and the Wideband Autocorrelation Radiometer (WiBAR) were deployed at the Keweenaw Research Center (KRC) from February to April 2020 to demonstrate these techniques. Results on snowpack brightness temperature and thickness measurements are presented and discussed.

This paper presents calibration procedure for time domain and frequency domain mode of wideband autocorrelation radiometry, (TD-WiBAR) and (FD-WiBAR), enhanced with a comb filter for RFI mitigation. WiBAR is a novel microwave method for measuring the thickness of low-loss layers, such as snow and ice packs. The time domain mode is faster than the FD-WiBAR, but requires its own calibration. We investigated a WiBAR enhanced with a comb filter in the laboratory with a data collected from a simulation circuit using a Keysight Spectrum Analyzer. The data are further post-processed for the time and frequency domain calibration. The comb filter is provided to mitigate radio frequency interference (RFI). RFI increases the noise floor and results in a decreased signal to noise ratio (SNR) delay peak in the autocorrelation function of the WiBAR from which the snow depth is extracted.

In this letter, a hybrid analytical and numerical simulation method is presented for the time-efficient calculation of bistatic scattering from the buried targets. This computation is used for a fixed transmitter and target location but for a moving receiver to generate the data set for a 3-D synthetic aperture radar (SAR) simulation. In this method, initially, the current distribution on the target when illuminated by the transmitter (in the absence of the receiver) is calculated. Then, the receiver is used as a transmitter and its field is calculated everywhere in the lower half-space. The reciprocity is then used to find the open-circuit voltage across the receiver terminals due to the equivalent current distribution on the target. This approach substitutesNfull-wave simulations forNsampling points required in SAR imaging with two simulations leading only to a factor ofN/2reduction in the simulation time. The proposed method is validated by comparing it with the brute-force full-wave simulation method as well as by image reconstruction from the data set generated by the method.

Through-the-wall imaging using wideband synthetic aperture radar (SAR) is a powerful tool that enables seeing through visually opaque walls by providing high-resolution images of objects behind the walls. Previous works focus on detection of static and moving point scatterers behind the walls and methods for enhancing the image by removing the effect of transmission through the walls. Besides imaging of hidden objects, detection of walls and large flat surfaces provides complete map of buildings’ interiors and enables better path planning and treat assessment in rescue and military operations. In the standard high-resolution SAR processing, walls and objects with large surface are imaged as discrete points instead of solid lines and as a result, without prior knowledge about the imaging area, walls may be interpreted as few discrete closely spaced targets. In this letter, a method is presented to discriminate walls and objects with large flat surfaces from other objects. In this approach, instead of focusing the synthetic radar beam on a point on the wall surface, the beam is focused at the location of the image of transmitter with respect to the wall surface considering only specular reflections. This is done by assuming there exists a wall at a distance from the transmitter with a known orientation. This results in an image in polar format in which locations of peaks determine the distance and orientation of the actual wall surfaces inside the imaging area. The method is applied to the measured SAR data and the results exhibit the capability of the method in detection of walls in real scenarios.

One of the fundamental technical challenges of any new spaceborne vegetation remote sensing mission is the determination of what sensor(s) to place onboard and what, if any, overlapping modes of operation they will employ as each onboard sensor adds significant cost to the overall mission. In this article, the remote sensing of forest parameters using multimodal remote sensing is presented. In particular, polarimetric radar, Light Detection And Ranging (LiDAR), and near-IR passive optical sensing platforms are employed in conjunction with physics-based models. These models are used to accurately estimate forest aboveground biomass as well as canopy height in homogeneous areas. It is shown that this proposed method is capable of achieving high accuracy estimates while using minimal ancillary data in the estimation process. We present a method to combine measured data sets with our geometric and electromagnetic sensor models to develop a forest parameter estimation algorithm that fuses multimodal remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure including dry biomass and canopy height with rms errors of 1.6 kg/m2and 1.68 m respectively.

Slope stability models developed based on the physical mechanism of landslides show the effectiveness in landslide probability assessment, while they have rarely been applied in the field of radar remote sensing. Inspired by the related work, this article proposes a new quantitative method for rainfall-induced landslide probability assessment based on safety factors (SFs) using soil moisture estimation from synthetic aperture radar (SAR) images. In order to combine slope stability models with SAR measurement, first, soil moisture that plays a vital role in slope stability models is estimated by SAR techniques from vegetated slope terrain. In this article, we propose a new SAR data processing model for potential landslide areas and a modified physical-based scattering model for short vegetation. The estimated results are qualitatively verified by the tropical rainfall measuring mission (TRMM) instrument and are quantitatively verified by the field investigation. Second, we study the water table level that plays another vital role in slope stability models and cannot be retrieved from SAR data. The analysis indicates that it can be treated as a constant in the case of unsaturated soil moisture. Combining with other geotechnical parameters that do not change with external circumstances, we simplify the slope stability model, of which effectiveness is tested by the visual interpretation. Finally, the SF maps are obtained by the simplified slope stability model using soil moisture estimated from the corresponding SAR images. The field investigation shows that all the observed landslides are located in the unstable areas, indirectly verifying the proposed method.

Electromagnetic scattering model from 3-D snowpack with arbitrary thickness is considered. A fully coherent model is presented through the usage of the Statistical S-Matrix Wave Propagation in Spectral Domain approach (SSWaP-SD). The computer-generated snow media is constructed using 3-D spatial exponential correlation function along with Lineal-Path function to preserve the connectivity of the snow particles as well. The SSWaP-SD in conjunction with a Method of Moments (MoM) code based on the discrete-dipole approximation (DDA) is chosen to leverage both the time-efficient computations of the DDA and the full-coherency of the SSWaP-SD method simultaneously. The SSWaP-SD depends on the discretization of the medium into thin slabs. Several realizations of a thin snow slab are solved numerically to form the statistics of the scattering matrix representing such a thin snow layer. For an arbitrarily thick snow layer, thin slabs of a snowpack are analyzed and a corresponding polarimetric N-port (representing different directions of scattering) S-matrix is generated. These S-matrices are cascaded using SSWaP-SD method to calculate the total forward and backward bistatic scattered fields in a fully coherent way. The simulation results of the backscattering from an arbitrary thick snow layer are presented and validated with measurements.

A new technique for measurement of the resonant frequency and Q-factor of resonators is presented. In this technique, the derivative of the insertion phase with respect to frequency of resonators are measured and used for the calculation of their resonance frequency and Q-factor. A slow-rate chirp signal is passed through a resonator, and the output signal is amplified and equally divided into two signals which are delayed by different amounts. The two delayed signals are fed to a phase detector measuring their phase difference. The derivative of the insertion phase with respect to frequency of the resonator can be simply found from the phase difference between the two delayed signals. The proposed measurement technique is realized using low-cost components and utilized for measuring the resonant frequency and Q-factor of several L-band resonators. Compared with the resonators' performance measured by a vector network analyzer, the introduced approach measures the resonant frequency and Q factor by less than 0.6% and 4% error, respectively.

This paper presents novel detection and target identification techniques for a polarimetic J-band millimeter-wave automotive radars. Three major target categories are considered, and extensive experimental and numerical data have been generated to find unique features of different target types. The response of vehicles is experimentally studied to build scattering maps for different kinds of cars. The radar backscatter response level from road surfaces is investigated and possible applications such as lane detection and road condition recognition are discussed. Sample results for each target type is presented to illustrate the suggested detection techniques. A method for micro-Doppler spectrum measurements of a moving human body is suggested as a very useful and unique feature to detect pedestrians in traffic scenes.

Pipeline detection is a problem with important applications in oil and gas pipeline transport systems maintenance. The scattering mechanism for extended targets such as pipelines is different than the scattering mechanism of localized targets which poses a challenge when trying to detect and image such targets using traditional imaging schemes such as back-projection algorithm. In this paper, a novel method for detection and estimation of pipeline depth, orientation and displacement is proposed. The method utilizes the unique way a pipeline scatters incident waves to find the actual bistatic path the signal takes and compensate for such path to focus the signals gathered by a moving receiver from the pipeline. The method is explained and preliminary results are presented as a proof of concept.

The global forests play a significant role in local and global ecosystems and as a result are the subject of remote sensing campaigns. Interferometric Synthetic Aperture Radar (InSAR) is a proven technology and is used to image foliage in a variety of daylight and weather conditions. InSAR relies on the collection of multiple SAR images either simultaneously with a single transmitter and multiple receivers separated in space or over time with a single transmitter and receiver observing a forest stand at different times. It is this repeat-pass operation that is of interest in this study as the delay between passes enables an observation of temporal deformations in a forest stand including the impact of wind. We present an approach to quantify the effect of wind on an InSAR system's ability to accurately estimate the canopy height of a forest stand. We propose to create a set of simulated trees and expose each to an impulse wind field. The geometry of each tree as it reacts to the incident wind field will be recorded and imaged by an InSAR simulator such that a temporal history of wind-affected geometries and their corresponding InSAR measurements will be recorded. From these measurements, a relationship between the tree height, mass, density, the simulated scattering phase center, incident angle, and incident wind field will be developed.

Wideband autocorrelation radiometry (WiBAR) is a newly developed microwave radiometric technique to remotely and directly measure the microwave propagation time difference of multipath microwave emission from low-loss layered surfaces, such as a dry snowpack and a freshwater lake icepack. The microwave propagation time difference through the pack yields a measure of its vertical extent. A major source of error in the measured thickness of the pack is due to the error in the measured time delay by WiBAR using the inverse Fourier Transform (IFFT) approach, which is an unbiased estimator of frequency. Using the Cramer-Rao lower bound (CRLB) on the variance of the estimator, it is shown that the variance of the estimated time delay would reach this minimum variance for signal to noise ratios (SNRs) higher than a threshold value, which depends on the detection scenario (lake icepack or snowpack), the window function, and the incident angle. It is also shown that the variance of the measured thickness is very high near the Brewster angle, as expected.

This paper presents a new method to suppress radio frequency interference (RFI) for a recently developed microwave radiometer technique, known as wideband autocorrelation radiometry (WiBAR). WiBAR is a method which can measure directly the thickness of a low-loss layer like lake ice or snow on the ground. However, the RFI in the received signal increases the noise floor and results in a decreased signal to noise ratio (SNR) of the WiBAR delay peak in the autocorrelation function. We propose a new filter which acts like a Fabry-Perot interferometer (FPI) in optics and has the frequency response of a comb filter with many evenly spaced alternating pass and stop bands. The response of an ideal comb filter applied to the polluted spectrum captured by WiBAR's receiver to mitigate the RFI in the received signal.

Electromagnetic scattering model from 3D snowpack with arbitrary thickness over a rough surface is considered. A fully-coherent model that accounts for multiple scattering among all particles and rough surface is presented through the usage of the Statistical S-Matrix Wave Propagation- in Spectral domain approach (SSWaP-SD). The SSWaP-SD technique represents each part of the medium into a statistical S- Matrix and these matrices are coherently cascaded at the end to get the full response. The computer-generated snow media is constructed using 3D spatial exponential correlation function along with Lineal-Path function to preserve the connectivity of the snow particles as well. The SSWaP-SD in conjunction with a Method of Moments (MoM) code based on the Discrete-Dipole Approximation (DDA) is utilized to get the scattering characteristics of an arbitrary-thick snow layer. The rough surface response is estimated through analytical technique (PO) and numerical solver (MoM-FEKO). The full response is then calculated by cascading the S-matrices representing the snow and the rough surface. The simulation results of the backscattering are presented and compared with measurement.

A new passive microwave remote sensing technique, wideband autocorrelation radiometry (WiBAR), directly measures the microwave propagation time difference of multipath microwave emission from low-loss layered surfaces such as a dry snowpack and a freshwater lake icepack. The microwave propagation time difference through the pack yields a measure of its vertical extent. However, the presence of variable pack thicknesses within a footprint of the radiometer's antenna will add complexity to the retrieved time delay. This issue is more severe for WiBAR on airborne and spaceborne platforms than WiBAR on ground-based platforms since the footprint for a given radiometer antenna is larger. From a simple forward model for a layer having distinct thickness values within one footprint (pixel), the system requirements for resolving these distinct thickness values are derived. A subpixel lake ice thickness distinction of 3.7 cm is demonstrated with an X-band WiBAR instrument at an incidence angle of 70°.

A novel ultrawideband directive antenna for ground-penetrating radar (GPR) applications is presented in this letter. The antenna is designed for operation at frequencies below 500 MHz to allow for high-depth-resolution imaging of the deeply buried targets such as buried pipes and other deep underground man-made structures such as tunnels. The antenna is formed by a pair of coupled antennas inspired by an electrically narrow very low profile (ENVELOP) antenna with differential feeding to provide a directive pattern normal to the antenna ground over a wide bandwidth. An antenna operating in the range of 140-510 MHz is designed and fabricated using the printed circuit board (PCB) substrates. The antenna is designed and optimized for operation in the proximity of a half-space soil medium to achieve efficient coupling of power from the air to the ground. The measured reflection coefficient of the antenna near concrete and wet soil covered by sand and grass is shown to be better than -9.5 dB within the specified band. The simulated realized gain of the antenna in the presence of dry soil is better than 4.9 dBi within the range of 140-510 MHz. The antenna is low-profile with a total height of 153 mm and a lateral dimension of 600 mm × 600 mm. The performance of the antenna for GPR applications is evaluated through a field measurement of a buried object in wet soil with high losses.

This article proposes an unsupervised multiregion segmentation method for fully polarimetric synthetic aperture radar (polSAR) images based on the improved fuzzy active contour model. Different from most of the active contour models that are based on the utilization of only statistical information, the proposed method makes better use of information from polarimetric data. In addition to the statistical information, an edge detector modified from the ratio of exponentially weighted averages (ROEWA) operator, a sliding window algorithm for the total received power, and a ratio operator with respect to scattering mechanisms are integrated to the proposed active contour model. We then present a layer-based fuzzy active contour framework to solve our model. The general fuzzy active contour framework is computationally much more efficient compared with the level set-based framework; however, it cannot be applied to the multiregion segmentation of SAR images due to its low robustness to strong noise. The proposed approach includes the advantages of the general fuzzy active contour framework and has good robustness. Using two fully polSAR images demonstrates that the proposed method can achieve higher efficiency and a better segmentation performance in comparison with the commonly used active contour methods.

The objective of this article is to investigate a multiphase segmentation framework for synthetic aperture radar (SAR) images, which is proposed based on the idea of the fuzzy region competition-based method. The fuzzy region competition-based framework is highly efficient and can attain good segmentation performances for conventional images. The framework is achieved based on its convexity, which not only ensures the existence of a globally optimized solution but also enables the convex optimization theory-based solving algorithms that are feasible. However, the constraint conditions of the framework that guarantee this convexity probably cannot be satisfied in the segmentation of images corrupted with strong noise. Therefore, applying this method to an SAR image probably produces an unsatisfactory segmentation result. To address this problem, we propose an improved fuzzy region competition-based framework in terms of the hierarchical strategy, such that the framework is always convex during the iterative calculation. The proposed framework inherits the advantages of the fuzzy region competition-based method, as well as that it is able to be applied to the segmentation of images with strong noise. Several experiments are then carried out to test and verify the performance and the robustness of the proposed framework. It demonstrates that the proposed segmentation framework can be applied to various types of SAR images and achieves satisfactory segmentation results.

In this paper, calibration of a high-resolution imaging SAR using an active point target is considered. Most of the time, the exact position of the calibration target with respect to the ground pixel cannot be determined ahead of time. As we show in this paper, an offset in the location of the calibration target with respect to the center of the ground pixel can result in a rather large calibration error if not properly accounted for. Furthermore, depending on the pixel size, the impulse response of the active calibration target may span over a long enough time to create aliasing effects over a few adjacent pixels. This paper will investigate both of these effects and introduce a method to accurately calibrate the SAR in the presence of these effects. It is shown that the proposed method also reduces the effect of clutter on the accuracy of calibration.

Physics-based Fully-Coherent Electromagnetic (EM) scattering model from 3D snowpack with arbitrary thickness is considered. The computer-generated snow media is reconstructed using the implementation of the Lineal-Path function in conjunction with 3D spatial exponential correlation function to assure the macroscopic connectivity of the snow particles. A fully-coherent EM computation is performed using the Statistical S-Matrix Wave Propagation- in Spectral domain approach (SSWaP-SD) along with a Method of Moments (MoM) code based on the Discrete-Dipole Approximation (DDA). This approach is chosen to leverage both the time-efficient computations of the DDA and the full-coherency of the SSWaP-SD method simultaneously. For an arbitrarily thick snow layer, thin slabs of a snow pack is analyzed a corresponding polarimetric N-port (representing different directions of scattering) S-matrix is generated. These S-matrices are cascaded using SSWaP-SD method to calculate the total forward and backward bistatic scattered fields in a fully coherent way. The simulation results of the backscattering from an arbitrary thick snow layer are presented.

Wideband autocorrelation radiometry (WiBAR) is a recently developed microwave radiometric technique to measure the lake icepack or snowpack thickness. This technique offers a direct method to remotely measure the microwave propagation time difference of multipath microwave emission from low-loss layered surfaces such as dry snowpack and freshwater lake icepack. The microwave propagation time difference through the pack yields a measure of its vertical extent. However, the lake icepack thickness measurement can be affected by the presence of a dry snowpack, which introduces another multipath interference. We present a simple geophysical forward model considering this effect and derive the WiBAR system requirements needed to correctly measure the icepack thickness. An X-band instrument fabricated from commercial-off-the-shelf (COTS) components is used to measure the thickness of fresh water lake ice at the University of Michigan Biological Station. The WiBAR was able to directly measure the icepack of about 36 cm with a snowpack of about 4 cm on top at incidence angle of 69.4° with an accuracy of 2 cm.

Through-the-wall radar imaging is a powerful tool for mapping buildings' interiors and hidden objects behind the walls. Through-the-wall imaging systems require large linear arrays of directive antennas to form a large aperture for obtaining images with a high cross-range resolution. However, the low mobility and limited field of view of the conventional systems limit their imaging capability. The concept of all-directions through-the-wall imaging has recently been proposed to enhance the mobility, cross-range resolution, and field of view of the through-the-wall imaging systems. In this technique, the large linear array of directive antennas is replaced by a dense 2-D synthetic array formed by small moving transceivers utilizing omnidirectional antennas. The 2-D synthetic array provides 360° high cross-range resolution images. This paper focuses on the implementation of a system realizing all-directions through-the-wall imaging and measurement results. A bi-static frequency-modulated continuous wave (FMCW) radar system utilizing a simple wireless synchronization scheme and wideband omnidirectional antennas is fabricated and an image formation technique compatible with bi-static FMCW imaging system is presented. Measurement results show that the imaging system can provide 360° high-resolution image of objects and walls in a short time.

This paper proposes radar sensors operating at J-band (220-320 GHz) for automotive applications. Operating at J-band, at about three times higher frequency than the currently available automotive radars operating at 77 GHz, will result in three-fold improvement in cross-range resolution for the same antenna size. Since the characterization of the radar backscatter from different objects on the traffic scenes is necessary for optimizing the design of automotive sensors, the work reported in this paper is the start of a broader study that attempts to fill the lack of knowledge on radar backscatter behavior of road environment at this frequency band. Considering vehicles as the most important object for automotive radars, this paper investigates the response of vehicles from different aspects. A combination of outdoor high-resolution synthetic aperture radar imaging experiments and real-aperture imaging measurements of vehicles are performed using a 222-GHz polarimetric instrumentation radar. The aim of these experiments is to identify the scattering centers on different vehicle bodies and to determine the statistics of the radar return. The results show that significant scattering is due to a limited number of fixtures on the vehicle's outer surfaces facing the radar. The strongest scattering phase-centers observed are due to specular reflections and, hence, have a strong dependence on the relative look angle. The statistics associated with backscatter from vehicles are found, in most cases, to best fit the Weibull distribution.

Autonomous driving system and intelligent transportation systems (ITS) become increasingly popular, which requires reliable and high-speed Vehicle-to-Vehicle (V2V) communications. In realistic road traffic environment, foliage is commonly seen and blocks the line-of-sight link. In this paper, semi-exact semi-closed-form models for the far-field as well as near-field scattering from a tree trunk are developed at 5.9 and 60 GHz. Extensive numerical evaluations on the scattering fields are presented. To make the results accessible to other users, curve-fitting functions are invoked to characterize the scattered field, and are attempted to extract a macro-model for the path loss, mainly as a function of the distance and azimuth angle. This work is promisingly useful for V2V millimeter-wave communications and radar sensing.

This paper summarizes the results of an extensive study to model the statistics of the polarimetric backscatter response of vehicles at 222 GHz. Radars operating at high millimeterwave frequencies provide the necessary high azimuth resolution envisioned for many advanced applications of automotive radars, including autonomous vehicles. The data of many polarimetric measurements of vehicles are used here to extract the statistical behavior of radar scattering from vehicles. It is found that the radar statistics for a given vehicle are different as the percentage of the illuminated area of the vehicle is changed. The Weibull distribution is found to be the best fit to all measured data, with its shape parameter adjusted for different types of vehicles, radar polarization, and percentage illumination area. The results reported in this paper should provide valuable information for developers of such radars to optimize the performance of their detection and classification algorithms.

Tracking carbon as it enters and exists each stage of the carbon cycle is necessary to help build understanding of the cycle's mechanics and its effect on climate. Satellite and airplane based remote sensing technologies have shown promising results in aiding in human understanding of our planet, including vegetative areas. The Harvard Forest has been studied in various ways over the course of the last century. In particular, synthetic aperture radar, LiDAR, and passive optical sensors have each been used to study the Harvard Forest. Employing a form of data fusion, we present an approach to estimate a forest stand's mean canopy height and biomass for each component tree species while employing minimal ground measurements. We present an approach where a database of simulated forest stands is generated containing both homogeneous stands and heterogeneous stands with up to four tree species present in a given stand. Each simulated stand is compared to an input stand on a number of criteria and a figure of similarity is calculated. In the case that a simulated stand isn't found with a figure of similarity below a set threshold, an iterative process is employed to modify the most similar stand to improve the factor of similarity by modifying the stand's species composition, tree densities, heights, and biomasses. A simulated stand, either pre-existing or developed dynamically will be considered a reasonable representation of the physical forest stand and the 3-D structure of the simulated stand will be reported as an estimate for that of the physical forest stand. This method relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We have previously investigated the ability of our method to differentiate between coniferous and deciduous trees in the same forest stand. We propose to extend this to a maximum of four different tree species, and to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.

This paper presents an L-band Single Antenna Polarimetric Active Radar Calibrator (SAPARC) designed and constructed at the University of Michigan in collaboration with the suborbital radar group of Jet Propulsion Laboratory. The SAPARC is intended for radiometric and polarimetric calibration of both airborne and spaceborne L-band radars, including the NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA-ISRO Synthetic Aperture Radar (NISAR). The presented Polarimetric Active Radar Calibrator (PARC) is designed to have a specific scattering matrix response (equal entries) and a very large and stable radar cross section (RCS) value which is significantly higher than its passive counterparts for providing a much higher signal-to-clutter ratio. The specific scattering matrix response enables the PARC to evaluate all the radar channels' radiometric calibration constants as well as cross-talk and channel imbalances, which cannot be estimated by the passive calibration targets. The much higher signal-to-clutter ratio provided by the PARC further reduces the residual errors of calibration and allows them to be easily deployed at different target scenes during radar data acquisitions.

Vegetation monitoring is important in earth science. It plays an essential role in biomass estimation, soil moisture retrieval, irrigation planning, and it also can help us better understand climate change, among others. Sentinel-1 data acquired since 2014 with a particularly short revisit period is well suited to monitor vegetation growth. In this paper, we analyze the temporal behavior of backscattering coefficients as well as the cross-pol ratio (VH/VV) of an agricultural area and a forest obtained from Sentinel-1A data. Normalized Difference Vegetation Index (NDVI) data derived from Landsat 8 data is used to roughly differentiate vegetated and non-vegetated areas. This study verifies the feasibility of Sentinel-1 data to vegetation monitoring, and gives the physical interpretation of the observed experimental results, which provides a useful information for the next phase of radar data applications, such as image classification.

Wideband autocorrelation radiometry (WiBAR) is a new method to remotely sense the microwave propagation time τdelayof multi-path microwave emission of low loss layered surfaces such as dry snowpack and freshwater lake icepack. The microwave propagation time τdelaythrough the pack yields a measure of its vertical extent; thus, this technique is a direct measurement of depth. However, the presence of a different low loss layer on the lake icepack such as dry snowpack introduces another multi-path interference, which can effect the lake icepack thickness measurement. We present a simple geophysical forward model for the multipath interference phenomenon and derive the WiBAR system requirements needed to correctly measure the icepack thickness. An X- band instrument fabricated from commercial-off-the-shelf (COTS) components are used to measure the thickness fresh water lake ice at the University of Michigan Biological Station. Ice thickness retrieval is demonstrated from nadir to 73.9°.

This paper presents a technique to reduce the specular reflection effect from the ground surface to an L-band dual-polarized Single Antenna Polarimetric Active Radar Calibrator (SAPARC) with high and stable RCS (55 dBsm) by the means of using a dihedral centered at the specular point. The SAPARC uses a single antenna and a precision Ortho-Mode Transducer (OMT) to isolate between transmit and receive paths. The system is designed to achieve a 30 dB signal-to-clutter ratio while operating in free space. Degradation of such high signal-to-clutter ratio happens due to the side lobe absorption of the specular reflection from the ground. To reduce the effect of such strong reflection, it is proposed to use a dihedral positioned at the specular point on the ground covering the Fresnel zone of the SAPARC antenna. The received field is reduced by an average of 25 dB over most of angular range of interest.

A computationally efficient and coherent electromagnetic scattering solution for a snow layer with an arbitrary thickness is considered in this paper. Several realizations of a thin snow slab are solved numerically using the Method of Moments (MoM) with the application of the Discrete Dipole Approximation (DDA) to form the statistics of the scattering matrix representing such a thin snow layer. For an arbitrarily thick snow layer, the whole layer is divided into thin slabs and each individual slab is represented with a corresponding S-matrix using a pseudo random generator and these S-matrices are cascaded using the Statistical S-Matrix Wave Propagation in Spectral Domain (SSWaP-SD) method to calculate the total forward and backward bistatic scattered fields in a fully coherent way.

A novel microwave radiometric technique, wideband autocorrelation radiometry (WiBAR), is introduced. The radiometer offers a direct method to remotely measure the microwave propagation time difference of multipath microwave emission from low-loss layered surfaces, such as a dry snowpack and a freshwater lake icepack. The microwave propagation time difference through the pack yields a measure of its vertical extent; thus, this technique provides a direct measurement of depth. It is also a low-power sensing method, since there is no transmitter. We present a simple geophysical forward model for the multipath interference phenomenon and derive the system requirements needed to design a WiBAR instrument. An X-band instrument fabricated from commercial-off-the-shelf (COTS) components measured the thickness of the freshwater lake ice at the University of Michigan Biological Station. Ice thickness retrieval is demonstrated from nadir to 59°. The WiBAR was able to directly measure the lake icepack thickness of about 36 cm with an accuracy of 2 cm over this range of incidence angles.

This paper presents a new single-antenna polarimetric active radar calibrator (PARC) intended for the polarimetric and absolute radiometric calibration of the NASA's soil moisture active passive (SMAP) radar. The PARC receives and retransmits the SMAP signal through a dual-polarized horn antenna with 17-dB gain at the center frequency of 1.26 GHz with 100 MHz of bandwidth. The transmit and receive polarizations are perpendicular and are isolated from each other using a precision orthomode transducer (OMT) specially designed for this application. The antenna is rotated 45° in the plane perpendicular to the direction of incidence, so that the scattering matrix of the PARC with respect to SMAP polarization coordinates has equal entries that enable radiometric calibration of all four channels simultaneously. As SMAP radar resolution is coarse (1 km), a point target with a very large radar cross section (RCS) is required to provide a high signal-to-clutter ratio. The proposed PARC can provide RCS values as high as 80 dBsm to achieve a 30-dB signal-to-clutter ratio. The PARC is controlled by a microcontroller to autonomously start minutes before the SMAP radar is expected to scan the area, stabilize the amplifier gain, record the magnitude of the pulses transmitted from the radar, and transmit these data to a base station. The design procedures of the OMT and the antenna, as well as control and RF circuits, are discussed, a number of leakage cancelation techniques are introduced to increase the isolation between the ports, the RCS of the fabricated PARC is fully characterized, and the image of the PARC as seen by SMAP is presented.

The paper reports on an extensive set of outdoor measurements aimed at characterizing the polarimetric radar backscatter response of vehicles at 222 GHz. This effort supports the future application of high frequency radars operating around 230 GHz in autonomous vehicle navigation and collision avoidance. It is observed that radar backscatter is primarily from the outer surfaces of the vehicle and that few strong scattering centers dominate the radar return. Derived radar statistics from reported data may be used by researchers in optimizing detection.

This paper reports on a set of radar experiments conducted at 222 GHz in support of envisioned application of radars to autonomous vehicles. The measured radar backscatter data of road surfaces at incident angles between 80 and 88oare presented. The polarimetric radar response level from different surfaces encountered in roads and highway environments and the angular dependency are discussed. The results are helpful in developing models for different surfaces and in the design process and assessment of autonomous vehicles sensors.

In this paper, a novel low-cost, reliable, and real-time telemetry technique in deep boreholes drilling is developed. This is accomplished by using the drilling pipe surrounded by the drilling mud as a Single Conductor Transmission Line (SCTL). A very compact transducer of dimensions 0.006λ×0.006λ×0.05λ (where λ is the free space wavelength) is designed for properly exciting a TM surface wave on the drilling pipe and drilling mud SCTL. Fitting the standard borehole size, the transducer comprises an open-ended helical conductor concentrically surrounding the drilling pipe and provides a transition from the coaxial line to the SCTL at low HF-band over 2% fractional bandwidth.

Data synergy or fusion is a mechanism whereby discrete types of data are used together to achieve a better understanding than was possible with each individually. Spanning over 30% of the Earth's landmass, the global forest plays a role in numerous planetary systems including the carbon cycle. The objective of this study is to couple simulated forest stands with measured datasets from various instruments to estimate a forest's mean canopy height and aboveground dry-biomass in large regions spanning many square kilometers. We present a method to combine measured datasets with our sensor models to develop a feature estimation algorithm that fuses multi-modal remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure including dry biomass and canopy height in a region spanning over 60 km2.

The global forest covers over 30% of the Earth's landmass and plays a critical role in a number of global systems including the carbon cycle. Developing methods to track the carbon flow into and out of forests is necessary to gain a complete understanding of the global carbon cycle and, in turn, its effect on the climate. Remote sensing technologies such as satellite based passive optical remote sensing and synthetic aperture radar are uniquely capable of interrogating forests. Using data fusion or synergy, we present a novel approach to estimating forest aboveground biomass and mean canopy height in heterogeneous forest regions with minimal required ancillary ground measurements. We present a dynamic database driven approach wherein a region of study is divided into stands and each stand is compared to a set of simulated forest stands. The simulated stands each contain a set of simulated fractal trees with distributions based on observed ranges within the area of study. Each stand within the region of study is examined and compared to the simulated forest stands using a measure of similarity. If a simulated stand is not found to be similar to the measured stand, an iterative process is employed wherein the most similar simulated stand is dynamically modified including its species composition and the mean canopy height and above-ground biomass within each species until a similar simulated stand is constructed. The simulated stand, regardless of if it existed previously in the set of simulated stands or if it needed to be dynamically generated, is considered a reasonable representation for the measured stand under test and its height and biomass are reported. This approach relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We propose to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.

This paper presents an unsupervised segmentation method based on the variational model for fully polarimetric Synthetic Aperture Radar (PolSAR) images. Considering that fully PolSAR images contain much more information than optical or single-channel SAR images, we used the characteristics vector of PolSAR images instead of statistical parametric models in the variational model. To fully utilize characteristics information, we propose a ratio operator with respect to scattering mechanisms and a sliding window algorithm for total received power. Combining these two operators with statistical information, the variational model with respect to an energy functional is defined and the segmentation is then achieved by solving such functional in terms of fuzzy membership functions and dual projection method. The experimental results indicate that the proposed method can attain a better segmentation compared with the classical cluster algorithm based on the complex Wishart distribution and the variation model only using statistical information.

Wideband autocorrelation radiometry (WiBAR) is a new method to remotely sense the microwave propagation time τdelayof multi-path microwave emission of low loss layered surfaces such as dry snowpack and freshwater lake icepack. The microwave propagation time τdelaythrough the pack yields a measure of its vertical extent; thus, this technique is a direct measurement of depth. This technique is inherently low-power since there is no transmitter in contrast to active remote sensing techniques. In this paper, the system design parameters and physics of operation of the WiBAR are discussed, and it is shown that the microwave propagation time can be readily measured for lake icepack at incidence angles away from nadir to at least 59.1°.

Current through-the-wall imaging systems rely on large arrays of directive antennas to map buildings' interiors and hidden objects with a high cross range resolution. This paper introduces a new technique for through-the-wall radar imaging in which instead of large antenna arrays which reduces the mobility of the system, a small number of moving transceivers with omnidirectional antennas is utilized to form a large synthetic array. This enables high mobility for the system and can provide 360° image of the building in a short time. Moving receivers sample the reflected signals at different positions and form a large synthetic array by applying a beam forming technique to the samples. A bi-static wideband FMCW system realizing the proposed method is introduced in this paper and a sample of imaging is presented. It is shown that using orthogonal circular polarizations can reduce the effects of double reflections in the image.

The numerical solution of the electromagnetic scattering from a thin layer of snow as a building block for a statistical solver is the major focus of this paper. Both Finite Element Method (FEM) and the Method of Moments (MoM) are used to calculate the power spectral density of the total fields due to an incident plane wave.

A very compact and conformal launcher for single conductor transmission lines (SCTLs) at the HF-band is presented. Also the concept of using drill pipes as the conductor of SCTL is introduced for the first time to satisfy the need for cost-effective and real-time data communication in drilling process. It is shown that a TM surface wave can be launched effectively making use of the drilling mud around the drill pipe. Provision of TM surface wave launchers that can fit within the borehole at both ends makes it feasible to transmit data over the drill pipe from downhole to the surface and vice versa. The launcher is composed of an open ended helical conductor which concentrically surrounds the drill pipe with appropriate pitch and length forming a compact surface wave launcher. Keeping its dimension smaller than 0.005λ × 0.005λ × 0.03λ, the proposed launcher provides 2% fractional bandwidth at low HF-band.

Data synergy or fusion is a mechanism whereby discrete types of data are used together to achieve a better understanding than was possible with each individually. Spanning over 30% of the Earth's landmass, the global forest plays a significant role in numerous planetary systems; the carbon cycle included. The objective of this paper is to couple simulated forest stands with measured datasets from various instruments to estimate a forest's mean canopy height and aboveground dry-biomass in regions where lidar measurements are sparse; we propose to create a virtual lidar instrument based on other readily available sensor measurements. We present a method to combine measured datasets with our sensor models to develop a classification algorithm that fuses multi-modal remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure including dry biomass and canopy height. We show the performance of our proposed method in regions lidar measurements as well as in regions lacking these measurements. Finally, we present our method using virtual lidar and show that there is minimal degradation in our estimation.

Data synergy or fusion is a mechanism whereby discrete types of data are used together to achieve a better understanding than was possible with each individually. While the DESDynI missions have been reduced and renamed, their original goal to fuse several sensor modalities to achieve an understanding of the global carbon cycle is still valid. Spanning over 30% of the Earth's landmass, the global forest plays a significant role in numerous planetary systems; the carbon cycle included. The objective of this paper is to couple simulated forest stands with measured datasets from various instruments to estimate a forest's mean canopy height and aboveground dry-biomass. We use existing datasets to develop and validate our fusion and extrapolation approach, which involves using our four sensor simulators, including our fractal-based tree geometry generator, in tandem with our in-house parameter estimation software which performs fusion and retrieval functions. We then use existing field and radarlidar-VNIR data for the Boreas southern study area to validate our simulators in this region and construct a large set of boreal trees for use in our fusion and extrapolation processes.

Data synergy or fusion is a mechanism whereby discrete types of data are used together to achieve a better understanding than was possible with each individually. Spanning over 30% of the Earth's landmass, the global forest plays a significant role in numerous planetary systems including the carbon cycle. This paper presents a novel approach to estimating forest aboveground biomass and mean canopy height with minimal required ancillary ground measurements. We present a dynamic database driven model wherein a simulated forest is generated on the fly and is iteratively modified to find not only the canopy height and biomass, but also to approximate the stand's species composition. This approach relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We propose to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.

A classifier based on the Least Square Support Vector Machine (LS-SVM) with Fruit Fly Optimization Algorithm (FOA) for polarimetirc Synthetic Aperture Radar (SAR) image classification is proposed in this paper. This method uses pixel-based information and region-based information as the features of land cover. The former one comes from the integration of multiple polarimetric parameters obtained by various polarimetric decomposition techniques, and the latter one is derived from the Grey Level Co-occurrence Matrix (GLCM). Kernel Principal Component Analysis (KPCA) is afterwards used to reduce the dimensionality of the multi-feature data. Additionally, this method uses LS-SVM as the classifier. Due to the fact that the classification performance is dependent on the input parameters of LS-SVM, FOA is adopted to obtain the optimized input parameters. Finally, compared with the method without using FOA and the supervised Wishart method, the classification performance of a fully polarimetric SAR image is much better by using the proposed method.

This paper presents a landslide prediction method based on soil moisture estimation obtained by fully polarimetric Synthetic Aperture Radar (SAR) data and surface topography acquired by Shuttle Radar Topographic Mission (SRTM). In order to solve the problem of geometric distortion caused by topography, the study area is classified as measurable and non-measureable areas in terms of the terrain slope with respect to the SAR flight path. The polarimetric backscattering coefficients are corrected through a polarization transformation that depends on the direction of the unit normal for each image pixel. Areas of tall vegetation are excluded. A radiative transfer model for short vegetation is used for soil moisture estimation assuming the surface roughness is a fixed parameter. A soil stability model with soil moisture and slope as a parameter is employed to predict landslide. Finally, the model is applied to the Radarsat-2 images acquired from Maoxian, China, and the extracted soil moisture data is compared with Tropical Rainfall Measuring Mission (TRMM) data for validation. The soil stability model is then used for determination of areas for high possibility of landslide.

A recently developed microwave radiometric technique, known as wideband autocorrelation radiometry (WiBAR), offers a deterministic method to remotely sense the propagation time τdelayof multi-path microwave emission of low-loss terrain covers and other layered surfaces. Terrestrial examples are the snow and lake ice packs. The microwave propagation time τdelaythrough the pack yields a measure of its vertical extent. We report measurements of the icepack on Lake Superior, and the snowpack at University of Michigan Biological Station (UMBS) in winter 2014 and 2015, respectively. The observations are done at frequencies from 7 to 10 GHz for icepack and 1 to 3 GHz for snowpack. At these frequencies, the volume and surface scattering are small in the packs. This technique is inherently low-power since there is no transmitter as opposed to active remote sensing techniques. In this paper the system design parameters of the WiBAR is discussed and it is shown that the microwave travel time within a dry snow pack and lake ice pack can be readily measured for a wide range of layer thicknesses observed during the experiment.

This paper presents the radar scattering phenomenology of arctic shallow lake ice. This is an important feature for monitoring the arctic climate for this purpose, a full-wave simulation model to analyze lake ice scattering that includes columnar air bubbles and rough interface is presented. The proposed model can handle complex interactions between high density air bubbles and rough ice surfaces. Based on this model, the scattering contributions from the rough ice/water interface and columnar air bubbles in the ice at C band are calculated. It is concluded that the roughness at the interface between ice and water is the dominate contributor to the observed backscatter.

In this paper electromagnetic scattering from 3D dense random media for application in radar remote sensing of snow is considered. The first step is the development of a faithful physical model of the snow medium. The proposed physical model of the snow is realized using 3D spatial exponential correlation function and Lineal-Path function to preserve the connectivity of the snow particles as well. Statistical S-matrix approach in Spectral Domain (SSWaP-SD) in conjunction with an FEM EM solver is then used to calculate the statistics of forward and backward bistatic scattered fields using Monte-Carlo simulations.

Subterahertz frequencies between 100 and 300 GHz remain an untapped portion of the frequency spectrum for many radar- and radiometer-based remote sensing applications. This can be attributed in part to the lack of knowledge of the phenomenology of signal interaction with terrain at these frequencies. This paper examines recently acquired polarimetric radar backscatter data of different types of surfaces using a newly constructed polarimetric instrumentation radar operating at 222 GHz. At this frequency bare surfaces such as asphalt and dirt are electrically rough with subsurface aggregate sizes comparable with the wavelength resulting in substantial volume and surface scattering. The data show strong backscatter responses from bare surfaces with angular dependence proportional to the cosine square of the incidence angle along with significant depolarization (between -8 and -4 dB). The data for vegetation-covered surfaces show weak dependence on incidence angle and appreciable depolarization (between -12 and -6 dB). Empirical models for bare and vegetation-covered surfaces are proposed.

Through-the-wall radar imaging systems are utilized for mapping buildings' interiors and detecting static and moving objects hidden behind the walls. The current techniques rely on large linear antenna arrays with directional radiation pattern for obtaining high cross-range resolution, and their imaging capability is limited by the low array processing gain and field of view. This paper introduces a new technique for through-the-wall radar imaging in which the linear array is replaced by a dense 2-D synthetic array formed by an ad hoc network of moving transceivers with omnidirectional antennas. Applying this method enables imaging of building interiors from outside or inside with 360° field of view. As receivers move, the direct and reflected signals from a stationary transmitter are sampled at different positions within the roaming domain, and by combining such signal samples using an appropriate beam-forming technique, a large and dense array is synthesized to provide an accurate radar map of the buildings' interiors and hidden objects in all directions. To increase the system dynamic range, the direct signals between the transmitter (Tx) and receiver (Rx) antennas are reduced, utilizing orthogonal polarizations for Tx and Rx. To improve the range resolution and reduce the background noise, a new method based on the generalized pencil of function method is proposed. This method can accurately detect the locations of the reflecting points within the image which, in combination with the standard back-projection focusing, provides high-quality radar images. A finite-element method for a simple building structure and ray tracing for a large 3-D building structure are used to evaluate the performance of the proposed method.

In this study, small perturbation method (SPM) and Kirchhoff approximation (KA) are incorporated into ray-tracing (RT) routines to model multiuser multi-input multi-output (MU-MIMO) channels formed on a rough dielectric terrain. The effect of surface roughness and correlation length, solid soil fractions, moisture content, link range, antenna height, polarization, radiation pattern, and carrier frequency are examined on received power, power delay and angular profiles, root mean square (RMS) delay and angular spread, coherence bandwidth, and coherence distance. Quantitative and qualitative analyses reveal that antenna directionality and terrain undulation and textural composition have significant impacts on the received signal power and channel multipath parameters and, hence, the performance of MU-MIMO terrain-based communication systems.

This paper examines recently measured polarimetric radar backscatter data of different types of bare and vegetation-covered surfaces at 222 GHz. Bare surfaces, such as asphalt, dirt, and concrete, are electrically rough with aggregate sizes comparable to the wavelength. This results in substantial volume and surface scattering. The data show strong angular dependence of the backscatter response from bare surfaces and significant depolarization between -8 dB and -4 dB. The data for vegetation-covered surfaces show weak dependence on incidence angle with appreciable depolarization between -12 dB and -6 dB.

The lower VHF band shows potential for reliable communications in low power, short range scenarios among near-ground nodes in both indoor and urban environments. Such scenarios are of great interest, for example, in military and search-and-rescue settings. Most prior work at low VHF focuses on modeling path loss at long range. In this paper, we study indoor/outdoor near-ground scenarios through experiments focusing on both line-of-sight (LoS) and non-LoS (NLoS), at ranges up to 200 meters. By transmitting tones and pulses from various locations in a realistic environment, we acquire channel data via a mobile data collection platform which gathers data at hundreds of different locations. We show that the measured channels have a nearly ideal scalar attenuation and delay transfer function, with minimal phase distortion, and little evidence of multipath propagation. We further confirm the absence of small scale fading by measuring bit error rate (BER) versus received signal-to-noise ratio (SNR) for QPSK transmission in an indoor setting. Using only timing and carrier estimation at the receiver, the resulting BER curves coincide with theoretical additive white Gaussian noise channel BER predictions.

Polarimetric synthetic aperture radar satellite and ground-based Ku- and X-band scatterometer measurements are used to explore the scattering mechanism for ice in shallow Arctic lakes, wherein strong radiometric responses are seen for floating ice, and low returns are evident where the ice has grounded. Scatterometer measurements confirm that high backscatter is from the ice/water interface, whereas polarimetric decomposition suggests that the dominant scattering mechanism from that interface is single bounce. Using Fresnel equations, a simple model for surface bounce from the ice/water interface is proposed, and its predictions are supported by experimental parameters such as co-pol phase difference, co-pol ratio, and the results of rigorous numerical modeling. Despite early research suggesting double-bounce scattering from columnar air bubbles and the ice/water interface as the dominant scattering mechanism in shallow lakes, this paper strongly supports a single-bounce model.

Resolution degradation in both the cross-range direction and range direction of SAR systems operating in sparse random media at millimeter-wave frequency is studied using a novel coherent propagation model that accounts for multiple scattering in the medium. For the purpose of demonstration, a 2D random medium composed of electrically large scatterers with high dielectric contrast and low surface fraction value is considered. The study is motivated by assessing the performance of future sub-millimeter-wave (sub-MMW) SAR systems with unprecedented imaging resolution working in a rainy environment. Monte Carlo techniques combined with a novel simulation algorithm called Statistical S-matrix Approach for Wave Propagation in Spectral Domain (SSWaP-SD) are used to efficiently characterize the resolution degradation of the SAR system. It is shown that the cross-range resolution degradation is severe for long distance wave propagation inside the random medium, while the range resolution degradation is much less.

In this paper we present a medium frequency (MF) band imaging system to estimate the sub-surface hydraulic fractures. We propose a helical dipole antenna for the borehole imaging application. The proposed antenna is loaded with a ferrite-bundle and is optimized to achieve an ultra-compact size to fit within a volume of λ0/1400 × λ0/1400 × λ0/35 while maintaining a relatively high efficiency of about 20%. The feeding network is designed to match the antenna input impedance with the frequency tunability. Based on the proposed antenna, a radio-wave technique for detecting fractured regions in subsurface rock layers is developed. Compared with conventional high frequency mapping system, the penetrating distance has increased to kilometers range due to the low propagation loss at MF band. The method is based on single-hole setup with separate transmitter and receiver antennas. The time-gating is performed to minimize the direct-link signals. Post-processing maps the conductivity contrast in the target area with a good resolution.

A high-resolution subsurface imaging technique based on distributed near-ground sensor networks that utilize ultrawideband waveforms in the very high frequency (VHF) range is presented. An accurate scattering model for a target buried in realistic subsurface environment, modeled as a vertically stratified medium, is presented first. Then an inversion technique that uses ultrawideband near-field focusing is described. The signal penetration depth as a function of frequency and various subsurface parameters is calculated based on the developed forward model. The imaging resolution as it relates to the accuracy of background retrieval is also analyzed. A semi-empirical soil dielectric model that is originally developed for the ultra high frequency band is modified and validated at the VHF range with measured results available in the literature. For a given soil textural composition and frequency, the model predicts the real and imaginary parts of the dielectric constant as a function of soil moisture content. This soil dielectric model is utilized to make the inversion more efficient. To address the challenge associated with the design of compact and ultrawideband VHF antennas, a scheme utilizing multiple antennas and reduced number of frequency points is proposed. The sensor arrangement both in terms of spatial distribution and polarization of each antenna as it relates to the lateral resolution, as well as minimizing the direct coupling between the Tx and Rx antennas, is analyzed. The proposed subsurface imaging approach is validated based on numerical techniques and a laboratory scale model measurement results.

High-resolution subsurface imaging and topography estimation in deserts is very useful in many applications such as oil-field and ground-water explorations and archaeological surveys. To address this problem, we previously developed a subsurface imaging interferometric synthetic aperture radar (InSAR) concept that can estimate the subsurface topography. However, the image resolution of such a system is rather limited by the current techniques available for SAR focusing and InSAR image coregistration as the propagation effects and phase-front distortion caused by the top layer are not accounted for. In this paper, we discuss different image aberrations that result from the top-surface topography, including geometric and defocusing distortion. The issue created by subsurface caustics and their effect on SAR imaging are discussed. We then present a new approach to estimating and correcting such aberrations. By using simulations and measurements, it is shown that up to an order of magnitude improvement in the subsurface image resolution as well as significant improvement on subsurface interferogram coherence can be achieved. The proposed approach is based on the application of a previously developed subsurface inversion algorithm and a newly developed fast subsurface InSAR simulator. The results are verified numerically using 3-D simulations of different sand-dune geometries and an experiment using scaled-model measurements under laboratory conditions.

The horizontal and vertical (3D) structure of Earth's forested ecosystems are of great significance to their ecological functioning and societal uses. An IfSAR approach is one methodology whereby a forest's structure and height in particular can be successfully estimated. Critical to the successful estimation is a high correlation between multiple SAR images. Regardless of a forest's location on the Earth, motion due to wind can significantly alter a forest's appearance to a radar system operating at L-band and so too decrease this necessary correlation. In order to investigate and quantize the decorrelation induced by the wind, we have developed a model that is capable of generating both a single-pass and repeat-pass interferometric SAR response of a forest including the application of a randomly oriented wind field. The simulation consists of multiple interconnected parts including the generation of fractal tree geometries, a wind simulator to apply variable wind forces to the generated trees, an electromagnetic model to allow us to calculate a fully polarimetric Single Look Complex value for the SAR return of the combined target, and an IfSAR processing algorithm capable of calculating a scattering phase center in the presence of wind. Results present polarimetric scattering phase centers and interferogram coherence as a function of wind speed. We further deconstruct our SAR processor to yield individual scatting mechanisms and their resultant scattering phase centers. This deconstruction allows for an accurate estimate of the underlying ground to be generated, even in the presence of a strong wind field.

In this paper we present a radio technique for detecting and measuring the extent of hydraulic fractures in subsurface rock layers using MF band. The method is based on transmission measurements among elements of vertical and horizontal arrays in the borehole before and after fracking process. To realize this system a novel super-miniaturized borehole antenna operating at 2MHz is also presented. The proposed antenna is based on a ferrite-loaded helical dipole antenna optimized to fit a volume λ0/1337 × λ0/1337 × λ0/80 while maintain a high radiation efficiency of about 10%.

This paper examines recently acquired polarimetric data of dry sand with a smooth air/sand interface at millimeter-wave (MMW) frequencies. The data characterize volume scattering from different types of sand as a function of the radar incidence angle, frequency, polarization, and particle size. The data show substantial volumetric response from dry sand at MMW frequencies with significant depolarization (between -12 and -7 dB). An empirical model is proposed and adapted for both smooth and 1-D periodic dry sand surfaces. Comparison between the expected volume scattering response of a dry sand medium with the surface scattering response of dry sand surfaces with rough interfaces shows that volume scattering is, in general, dominant, particularly at 95 GHz.

One of the most fundamental new technical challenges of a DESDynI-R space-borne mission is the fusion of the several sensor modalities, including the onboard SAR and external LiDAR and Optical sensors in order to accurately estimate desired 3D vegetation structures and biomass parameters in areas where the sensors overlap. The objective of this paper is to use measured datasets in conjunction with our sensor models to develop a classification algorithm that fuses multi-modal remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure including dry biomass and canopy height.

This paper examines recently acquired polarimetric data of dry sand with smooth air/sand interface at MMW frequencies. The data characterizes volume scattering from different types of sand as a function of the radar incidence angle, frequency, polarization, and particle size. The data shows substantial volumetric response from dry sand at MMW frequencies with significant depolarization (between -12 and -7 dB).

In this paper, a theoretical platform for analysis of radar cross section of a finite stratified dielectric cylinder, representing a tree trunk, above a smooth distributed rough surface, representing the terrain, using reaction theorem is demonstrated. In this analysis, the second order interaction between tree and terrain (multiple scattering term) is included in the modeling platform to enhance the accuracy of the forward analytical model. An extensive set of Monte Carlo simulations have been utilized to calculate and validate the average scattered power (coherent and incoherent terms) against analytical model.

Radar imaging of deserts suffers from insufficient radar backscatter at low microwave frequencies due to the low permittivity of dry sand and relatively smooth sand surface roughness. Operating at millimeter-wave (MMW) frequencies, however, rectifies this deficiency as significant radar backscatter is generated by surface and volume scattering. This is due to the fact that sand surface roughness is electrically large and signal penetration into the dry sand, which is a homogeneous mixture of air and sand particles with dimensions comparable to a fraction of a wavelength, generates considerable volume scattering. This paper investigates both surface and volume scattering from dry sand surfaces, subject to the peculiar physical properties of sand surfaces found in sand dune-covered regions. An incoherent model is proposed that characterizes the angular dependence of volume scattering from dry sand in the presence of a 1-D rippled air/sand surface. A set of indoor experiments conducted on smooth and 1-D rippled sand surfaces at Ka-band confirms that significant volume scattering is present at MMW frequencies and that the proposed model correctly captures the observed angular dependence when 1-D surface ripples are present.

In this paper, the Doppler spectra of the radar backscatter response of human body and a quadruped are presented at W-band frequencies. This study is motivated by the desire to utilize millimeter-wave radars to detect pedestrians against other targets in the radar scene. The approach is based on dissecting the radar backscatter to isolate the radar returns from different body parts. The forward model is based on an iterative physical optics approach. The complex motion of different parts of walking bodies and their amplitude and range of motion is directly reflected in their radar cross section (RCS) and Doppler spectrum bandwidth. It is shown that the Doppler spectra and RCS differences are sufficient to distinguish a walking human from stationary and other moving objects. Radar polarimetry in conjunction with time-frequency analysis is examined as a method for detecting concealed carried objects. The overall backscatter is decomposed into components associated with the limbs and torso which are then utilized to enhance target detection.

One of the most fundamental new technical challenges of a DES Dynl space-borne mission is the fusion of the several sensor modalities LiDAR, SAR, InSAR, and Optical in order to accurately estimate desired 3D vegetation structures and biomass parameters in areas where the sensors overlap, and to extrapolate them over continuous areas where lidar data is absent. The objective of this paper is to use measured datasets in con junction with our sensor forward models to develop and validate an estimation algorithm that fuses various remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure, including biomass, canopy height, and tree species.

A high resolution subsurface imaging approach based on near-ground sensor networks operating in the VHF range that utilize ultra-wideband near-field focusing was recently proposed [1]. An accurate scattering model for targets buried in realistic subsurface environment modeled as a vertically stratified medium as well as an efficient inversion technique using an UWB near-field focusing were proposed. Numerical models were used to analyze the signal penetration depth in the VHF range and validate the proposed technique for targets that are buried at various depths [2]. In this paper, in order to investigate the performance of the proposed approach under practical limitations, laboratory-based scale model measurement results are utilized. In addition, various non-uniform sensor arrangements are tested to get an insight into how to best arrange a given number of sensors to cover the largest possible area and obtain the best possible lateral resolution.

Recently we proposed a new technique for subsurface topography estimation in deserts and arid regions using dual-frequency Interferometric Synthetic Aperture Radar (InSAR). One of the main concerns was the use of conventional SAR focusing techniques for imaging the subsurface region which can result in significant image degradation and lower limit on the minimum achievable azimuth resolution. In this paper we demonstrate the different image distortion effects that can appear in scenarios where top surface is non-planar. These effects include geometric distortion and dispersion of the point spread function. We then demonstrate how most of these effects can be corrected through the application of an iterative approach using an algorithm recently developed for subsurface topography estimation. Using scaled model measurements under laboratory conditions and 3D simulations of actual top layer topographies it is shown that the correction algorithm renders better azimuth resolution, improved geometric projection and significant improvement in interferometric coherence.

This paper analyzes and develops new approaches for handling and shaping collections of microscale objects such as particles or cells. While traditional dielectrophoretic manipulation approaches are based on creating an energy trap, this work employs a distributed manipulation philosophy: shaping the energy field to model the point-wise forces and hence the characteristics of the field. This method offers a better perspective on the behavior, exact shape, position, and orientation of the collection of objects under manipulation. Furthermore, this research showcases devices that artificially generate planar quadratic and squeezing force fields by setting the potential at each point in space. These devices enable the positioning of particles and collections of particles to a predefined shape and orientation. Finally, we demonstrate a novel approach to distributed manipulation. We construct a 3-D potential force field by setting the boundary conditions of the differential equation describing the dynamics of a natural medium (the voltage profile in our case). This approach is illustrated by constructing cylindrical and ellipsoidal potential force fields for use in particle and cell manipulation.

One of the most fundamental new technical challenges of a DESDynI spaceborne mission is the fusion of the several sensor modalities - LiDAR, SAR, InSAR, and Optical - in order to accurately estimate desired 3D Vegetation structures and biomass parameters at their point of intersection and to extrapolate them over continuous areas. The objective of this paper is to use both our simulation models and measured dataset to develop and validate fusion and extrapolation methods while simulating DESDynl-type missions. We use existing datasets to develop and validate our fusion and extrapolation approach, which involves using our four sensor simulators, including our fractal-based tree geometry generator, in tandem with our in-house parameter estimation software which performs fusion and retrieval functions. We then use existing field and radarlidar-VNIR data for the Boreas southern study area to validate our simulators in this region and construct a large set of boreal trees for use in our fusion and extrapolation processes.

The horizontal and vertical (3D) structure of Earth's forested ecosystems are of great significance to their ecological functioning and societal uses. An IfSAR approach is one methodology whereby a forest's structure and height in particular can be successfully estimated. Critical to the successful estimation is a high correlation between multiple SAR images. Regardless of a forest's location on the Earth, wind and precipitation can significantly alter a forest's appearance to a SAR system operating in either the L or C bands and so too decrease this necessary correlation. In order to investigate and quantize the decorrelation induced by factors such as wind and rain, we have developed a model for the repeat-pass interferometric SAR response of a forest including the application of a wind field and / or a rain storm. The simulation consists of multiple interconnected parts including the generation of fractal tree geometries, a wind simulator to apply apply variable wind forces to the generated trees, an electromagnetic model to allow us to calculate a Single Look Complex value for the SAR return of the combined target, an image forming technique based on antenna array theory, and an image processing algorithm. Results present polarmetric coherence as a function of platform look angle, wind speed, and moisture content. An important feature of this research is the usage of a physically based realistic wind model that is based on measurements of wind effects on trees as well as realistic models of fluid flow and simple harmonic branch segment resonators. Allowing branches to bend and move out of the plane of the incident wind field enables our model to capture numerous features of a physical tree blowing in the wind. This realistic model is necessary for a realistic simulation of the effects that wind has on a given InSAR imaging system as expressed in this study by the interferometric coherence.

The concept of a subsurface imaging technique based on Unattended Ground Sensor Networks operating in the VHF range using ultra-wideband waveforms was recently proposed in. In this approach a forward model for realistic subsurface environment based on the Dyadic Green's function for a stratified medium and an inversion technique using an ultra-wideband near-field focusing were presented. Simulation results showed that very good lateral and depth resolution could be achieved. Before carrying out an experiment to test the proposed technique, three vital aspects of the work which are imposed by practical limitations are investigated and presented in this paper. First, the sensitivity analysis to assess the signal penetration depth in realistic subsurface environments for various frequencies is performed. Analysis of the frequency requirements of the inversion as they relate to depth resolution is also analyzed. A semi-analytic soil dielectric model originally devised for microwave frequencies is extended to VHF and validated using measurement results available in literature.

Fully polarimetric measurements of volume scattering contribution from dry layer of fine sand with smooth air/sand interface were performed at millimeter-wave frequencies. The measured radar response was compared to predictions made by the numerical solution of the DMRT model. Sand particles were modeled as spherical particles. The simulated response was able to predict the angular dependence of the data but was not able to predict accurately the absolute level, especially for the cross-polarized return. Furthermore, a simpler model, which was developed earlier for asphalt surfaces and is based on 1storder solution of RT for semi-infinite medium, was tested against the measured data. The model was not able to predict the angular dependence demonstrated by the measured data.

In this paper, accurate tree stand height retrieval is demonstrated using C-band Shuttle Radar Topography Mission (SRTM) height and ancillary data. The tree height retrieval algorithm is based on modeling uniform tree stands with a single layer of randomly oriented vegetation particles. For such scattering media, the scattering phase center height, as measured by SRTM, is a function of tree height, incidence angle, and the extinction coefficient of the medium. The extinction coefficient for uniform tree stands is calculated as a function of tree height and density using allometric equations and a fractal tree model. The accuracy of the proposed algorithm is demonstrated using SRTM and TOPSAR data for 15 red pine and Austrian pine stands (TOPSAR is an airborne interferometric synthetic aperture radar). The algorithm yields root-mean-square (rms) errors of 2.5-3.6 m, which is a substantial improvement over the 6.8-8.3-m rms errors from the raw SRTM minus National Elevation Dataset Heights.

This paper presents an interferometric synthetic aperture radar (InSAR) system to map the bedrock topography underneath the sand in deserts and arid areas. This is anticipated to greatly increase the efficiency of oil field and ground water exploration as well as environmental and archaeological studies. The proposed system consists of two InSAR subsystems, one operating at Ka-band to map the sand topography and the other operates in the VHF band to map the subsurface topography. The different issues associated with InSAR processing for subsurface mapping are discussed. It is shown that conventional InSAR processing produces unacceptable error in height estimation since it does not account for the refraction and the different propagation velocity in the sand. Thus, a new inversion algorithm is developed which can be used to accurately estimate the bedrock topography for arbitrary sand and bedrock geometries. A sensitivity analysis is then presented to show the effect of the different systematic and random errors. The inversion algorithm is verified experimentally for flat sand case using a scaled model that was implemented in the lab.

A coherent scattering formulation is developed for radar remote sensing of Sahelian grassland. This African vegetation is mainly composed of annual grass and shrubs. In the proposed procedure, first, atemporalmodel for generation of grass and shrub structures, which includes important realistic botanical information, is implemented. Because we develop a coherent scattering model, preserving the relative position of plant elements in a statistical manner as accurately as possible is very important. Shrubs are reproduced using cylindrical elements which represent trunks, branches, and thin green stems that function as leaves for these shrubs. Their crown shape is highly irregular, but for the most part can be encompassed in an ellipsoidal or cylindrical volume; on the other hand, the grass is represented as a set of cylindrical stalks and blade leaves. The scattered power from each grass element is added because multiple scattering among adjacent elements can be neglected at microwave frequencies. We calculate the soil scattering using the Integral Equation Method and neglect the soil volume scattering which may become significant for dry soil condition at high incidence angles. Backscatter statistics are acquired via a Monte Carlo simulation over a large number of realizations. The accuracy of the model is verified using measured data acquired by the C-band environmental satellite advanced synthetic aperture radar instrument at different incident angles.

The horizontal and vertical (3D) structure of Earth's forested ecosystems are of great significance to their ecological functioning and societal uses. An InSAR approach is one methodology whereby a forest's structure and height in particular can be successfully estimated. Critical to the successful estimation is a high correlation between multiple SAR images. Regardless of a forest's location on the Earth, wind can significantly alter a forest's appearance to an L-band SAR system and so decrease this necessary correlation. In order to investigate the wind-induced decorrelation, we have developed a model for the repeat-pass interferometric SAR response of a forested area taking into account wind effects. The simulation consists of multiple interconnected parts including static tree geometry's generation, a wind simulator to apply to a static tree, and an electromagnetic model to allow us to calculate the interferometric SAR response. The static tree geometry generation process generates a pseudo-random tree based on a given DNA file which specifies a species specific structure. This geometry is then modified by the wind simulator producing snapshots of tree-geometry as a function of time. Each snapshot is then used in the interferometric SAR simulator to synthesize the wind-blown geometry's InSAR response. Results present coherence as a function of wind speed and forest structure. An important feature of this research is the usage of a physically based realistic wind model that is based on measurements of wind effects on trees as well as realistic models of fluid flow and simple harmonic branch resonators. Allowing branches to bend and move out of the plane of the incident wind field enables our model to capture numerous features of a physical tree blowing in the wind. This realistic model is necessary for a realistic simulation of the effects that wind has on a given InSAR imaging system.

A realistic forward model based on a near-ground distributed sensor grid for a target buried under soil is devised. The soil medium is modeled as a planar stratified medium with a complex dielectric constant profile. The Dyadic Green's function for multilayer dielectric is used to compute the electric field at the target. A high resolution inversion algorithm based on phase-conjugation approach to detect deeply submerged targets is also presented. The sensor network is setup to enhance the lateral resolution by forming a synthetic aperture. The depth resolution is improved by using bandwidth. So as to improve the efficiency of the search algorithm a soil dielectric model to predict the real and imaginary parts of the dielectric constant from the volumetric soil moisture for a given soil textural composition is extended to the frequency of interest (VHF) resulting in less number of variables.

This paper presents the application of Interferometric Synthetic Aperture Radar (InSAR) to estimate the height of the sand layer on top of the bedrock in deserts. This is anticipated to greatly increase the efficiency of oil field search and can have several applications for environmental and archaeological studies. The extension of InSAR processing to estimate the covered bedrock height through an iterative algorithm is introduced. The sensitivity of the proposed algorithm to system errors is investigated and its application to a common type of sand dunes is also presented.

Many realizations of foliage around a hard target are run to obtain the statistical variations of foliage and target responses. This is accomplished by using a hybrid target-foliage model, developed for the investigation of the scattering behavior of metallic targets embedded inside a forest canopy. This model is based on the coherent scattering theory of wave propagation through the foliage and an iterative physical optics approximation of scattering from the target. The model is capable of accounting for the first-order near-field interactions between the hard target and the foliage. Fully polarimetric simulation results of a foliage-camouflaged metallic target having complex geometry are generated at 2 GHz, and a polarization synthesis optimization method for improving signal-to-clutter ratio is carried out by applying genetic algorithms.

The 15 papers in this special issue focus on remote sensing of building interior and can be categorized into: 1) system design and instrumentation; 2) advanced imaging techniques for elimination of glint from large flat wall structures; 3) radar polarimetry; 4) passive microwave radiometry; 5) advanced forward models based on high-frequency methods as well as full-wave solutions based on finite-difference time-domain technique for large-scale problems; and 6) detection and identification techniques of behind the wall stationary and moving concealed and unconcealed targets.

An algorithm for imaging of targets behind walls is proposed to reduce the wall reflection and enhance the signal-to-clutter ratio. The image formation is based on differential synthetic-aperture-radar image formation employing a continuous-wave radar system. In this approach, instead of using individual backscattered signals, the image is formed by employing the difference signals obtained by subtracting two successive signals along the track. This way, specular reflections are totally eliminated without the need for the knowledge of the wall parameters. This also affects the point target response which is corrected by an integration process. By using backscattered fields from small trihedral corner reflectors behind a poured concrete wall, measured over a frequency band of 1-2.5 GHz, the proposed method is demonstrated.

In this paper, the applicability of a procedure for retrieval of vegetation parameters using a coherent scattering model that considers the botanical properties of Sahelian grassland and a stochastic optimization algorithm is studied. This African vegetation is mainly composed of shrubs and grass. Since the coherent scattering model is computationally time-consuming, a simplified empirical model is constructed by fitting of simulation results obtained by the scattering model. Inputs to the empirical model are the sensitive parameters that, for the studied class of vegetation, are the soil moisture content, grass density, and grass moisture content. The model outputs are the polarimetric backscattering coefficients as a function of the incidence angle. Employing the empirical model and a genetic algorithm, a search routine is implemented to estimate the biophysical parameters of the African vegetation from a data set of backscattering coefficients. The estimation of Sahelian-grassland parameters using the set of C-band HH-polarized measured data shows that this procedure achieves good agreement with the ground-truth data.

In this paper a physics-based approach for image formation of targets behind complex wall structures is presented. Analytical and numerical techniques are used for the development of forward scattering models which are then exploited in construction of matched filters for ultra-wideband synthetic aperture radars operating over a wide rang of incidence angles. Special scattering models for different wall types including cinder block and reinforced concrete walls are presented using efficient numerical and approximate analytical techniques. These allow for construction of SAR images as well as development of a refocusing algorithm. An experimental ultra-wideband radar is set up in the laboratory environment for the evaluation of the models presented. Also, a radar measurement configuration is proposed that allows for elimination of direct reflection from the walls.

In recent years a special emphasis has been placed on the retrieval of physical parameters from polarimetric radar at microwave frequencies in many research programs. In this paper, we adapted a technique based on an empirical model and a genetic algorithm, and verify its applicability for a complex class of vegetation within a wide temporal interval. This complex class of vegetation is Sahelian grassland which is mainly composed of annual grass and shrubs. The proposed retrieval algorithm is conformed of 3 main steps: (1) Identification of sensitive parameters, (2) Development of the empirical model, and (3) Implementation of a genetic algorithm for the inverse process. For this class of vegetation the sensitive parameters are: the soil moisture content ms, the grass density D, and the grass moisture content mv. When applying the retrieval algorithm to simulated radar responses, a great agreement (an error of 6% when estimating the soil moisture content, 13% for the grass density, and 18% for the grass moisture content in the adult-plant stage) is observed between input parameters and estimated ones.

Through-wall imaging/sensing using a synthetic aperture array technique is studied by employing ultrawideband antennas and for wide incidence angles. The propagation through building walls, such as brick and poured concrete in response to point sources near the walls, is simulated by using high-frequency methods. Reciprocity is used to find the responses of point targets behind walls, which are then used to simulate the synthetic aperture radar (SAR) imaging through the walls. The effect of building walls on the target-image distortions is investigated by simulations and measurements. It is shown that by using the idea of match filtering, the effect of the wall can be compensated for, and the point target response can be reconstructed, provided that the wall parameters are known. An optimization method based on minimization of squared error in the SAR image domain within an area confined within the expected point-spread function is used to estimate the wall parameters and sharpen the image simultaneously. A controlled experiment within the laboratory environment is performed to verify the methods presented. It is shown that for an ultrawideband system operating over a frequency band of 1-3 GHz, highly distorted images of two point targets in close proximity of each other behind a wall can be resolved after refocusing. A dual-frequency synthetic method is also presented that can improve the cross-range resolution of the refocused image.

Through-wall imaging using synthetic aperture array technique is studied by employing ultra-wideband antennas and for wide incidence angles. The effect of the building walls on the target image distortions is investigated by simulations and measurements. It is shown that using the idea of match filtering, the effect of the wall can be compensated for and point target response can be reconstructed. A controlled experiment within the laboratory environment is performed to verify the methods, presented. It is shown that for an ultra-wideband system operating over frequency band of 1-3 GHz highly distorted images of two point targets in close proximity of each other behind a wall can be resolved after refocusing. A dual-frequency synthetic method is also presented that can improve the cross- range resolution of the refocused image.

This paper investigates the performance of pseudo-noise (PN) sequences as pulse compression waveforms in the radar imaging of distributed targets. Multiple transmitter schemes such as multi-static synthetic aperture radar (SAR) and multi- baseline interferometric SAR (InSAR) provide high resolution images for remote sensing applications at lower costs. PN sequences are a natural choice for such systems. The performance of different PN coding schemes such as the maximal length sequences (m-sequences), Gold sequences and shifted m-sequences are compared.

A high-order accurate and efficient full-wave, 2D numerical algorithm is exploited to analyze electromagnetic waves propagating over irregular terrain. The algorithm derives its accuracy from the use of a locally corrected Nyström scheme for discretizing the PMCHWT combined field integral equation, and its efficiency from the use of a fast multipole technique for speeding up the evaluation of far field interactions. The convergence rate of the solution is fully controllable, which renders the solver an attractive tool for simulating long-distance, overterrain propagation and diffraction phenomena; for example, it is demonstrated that solutions with 8 digits of precision can be attained with as few as 8 surface discretization points per wavelength for a 1000-wavelength terrain profile.

A coherent scattering formulation is developed for radar remote sensing of Sahelian grassland. This African vegetation is composed of shrubs and annual grass. The proposed model includes a vegetation generator tool in order to create vegetation structure with realistic architectures and botanical information. This is important in the development of the coherent scattering model, since the relative position of plant elements needs be preserved as accurately as possible. To correctly account for the coherent attenuation through the crown layer, the crown shape of shrubs must be considered. The crown shape is highly irregular, but for the most part can be encompassed in an ellipsoidal or cylindrical volume depending on the ground truth data. Thus, the extinction of the coherent wave is then calculated only when traveling within the crown volume. On the other hand, the grass generator models the grass as a set of cylindrical stalks and blade leaves arranged in a semi- deterministic fashion. Since grass blades are thin, multiple scattering among adjacent elements can be neglected at microwave frequencies. Backscatter statistics are acquired via a Monte Carlo simulation over a large number of realizations. Depending on the season, it is shown that contribution from soil and grass are the dominant components of the overall backscatter.

The validity of a coherent Sahelian-grassland scattering model is determined by comparing the model predictions with satellite measurements of a representative site. This model considers the realistic botanical structure of grassland. The site Agoufou, located in the Northern Mali, was selected as the test target. This site is governed by a semi-arid tropical climate. Its vegetation is mainly composed of shrubs and annual grass. HH polarization backscattering data was collected over an entire growing season at different incidence angles by means of the ENVISAT ASAR. Simulations provided by the coherent model show a good agreement with measured data having a correlation coefficient equal to 0.92. Model predictions show that the HH polarization component is higher than the W polarization component during all growing season. Significant parameters are shown to be the grass density, the soil moisture content and the grass moisture content. The most sensitive parameter is the ground soil moisture content. Moreover, it is observed that the variation of the backscattering coefficient for all parameters can be represented by a linear regression function.

This paper discusses the design and construction of a compact, ultrafast, monostatic frequency modulated continuous wave (FMCW) millimeter-wave radar, operating at 94.75 GHz, intended to be used as a helicopter assisted landing sensor. A high speed direct digital synthesizer is used to generate the baseband FM signal. Custom transmitter/receiver baseband boards are designed to up/down-convert the frequency modulated (FM) signal to an appropriate IF before it can be connected to the W-band RF frontend. A high-gain lens horn antenna is used in the RF frontend, in conjunction with other waveguide-based W-band components. A Xilinx FPGA is used in the backend data processing, preferred over conventional DSPs because of its speed. The whole system is packaged in an aluminum casing, with dimensions of 9' x 11' x 11' and weighing under 20 lbs.

This paper discusses the development of an algorithm used to simulate the effectiveness of millimeter-wave radar in imaging a rough terrain, for the purpose of helicopter assisted landing. Using an externally generated terrain and the physical optics approximation, the algorithm computes the backscatter response of the terrain when illuminated by a real aperture antenna. Results are presented from simulating terrains with different macroscopic features, such as a hump, ditch or a slope. It shown that operating at millimeter-wave, more specifically at W-Band frequencies, is ideal for such an application where a compact sensor is required to achieve high resolution imaging.

Presents the winners of the 2006 IEEE Geoscience and Remote Sensing Society's (GRS-S) Awards, including the IEEE Fellow Awards, the Distinguished Achievement Award, the Outstanding Service Award, the Education Award, and five Paper Awards.

In this paper we use Finite Difference Time Domain (FDTD) numerical technique and Physical Optics (PO) approximation in conjunction with phase conjugation method, for computation of transmitted field through walls and image formation. Using this model, different refocusing techniques can be investigated. Numerical results for imaging of target behind a solid block wall and cinder block wall are provided.

In this paper, a hybrid target-foliage model based on existing electromagnetic techniques is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy at high frequencies. The proposed model is composed of two basic scattering models, one for foliage and the other for the hard targets. The connection between these two models, which accounts for the interaction between the foliage scatterers and the target and vice versa, is accomplished through the application of the reciprocity theorem. Wave penetration through the forest canopy and near-field and far-field scattering from the canopy's constituents is calculated using a coherent discrete scattering model that makes use of realistic tree structures. Calculation of scattering from a hard target illuminated by the reduced incident field and the scattered field of nearby vegetation is carried out using an iterative physical optics (PO) method formulated for fast computation of foliage-target interaction. To reduce the number of iterations, geometrical optics (GO) approximation is initially used for determining the shadowed areas over the hard target when illuminated by individual foliage scatterers. Furthermore, using a scaled measurement system at millimeter-wave frequency, the accuracy of the iterative PO model is demonstrated, employing a complex target that occupies a volume as big as 86lambdatimes33lambdatimes20lambda

A hybrid target-foliage model is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy. The proposed model is composed of two existing electromagnetic-scattering models, one for the foliage and the other for the hard targets that are coupled in a computationally efficient manner. The connection between these two models, which accounts for the interaction between the foliage scatterers and the target, is accomplished through the application of Huygens' principle. Wave penetration through the forest canopy and near-field and far-field scattering from its constituents is calculated using a coherent single-scattering theory, which makes use of realistic tree structures. Defining a Huygens' surface enclosing the hard target and calculating the illuminating field (the scattered fields from the nearby vegetation scatterers and reduced incident field), the interaction between the foliage and the hard target is accounted for. Computing the scattered field from target on the Huygens' surface and using a reciprocity theorem target-foliage interaction is captured very efficiently. Calculation of scattering from a hard target is carried out using a finite-difference time-domain (FDTD) technique. For a typical vehicle dimensions, the required time and memory for the FDTD computation and exact field calculation inside the foliage limits the simulation frequency to upper very high frequency (VHF) band

Abstract — In this paper an electromagnetic scattering model is presented that allows simulation of radar response from hard targets embedded within a foliage canopy. The modeling approach is based on a hybrid foliage propagation and scattering method and a full-wave simulation for a finitesize target. The hybrid model allows for inclusion of effects of foliage attenuation and scattering in addition to near-filed foliage-target and targetfoliage interactions. The purpose of developing this model is to investigate the effect of foliage on target signature and determine methodologies that would enhance target detection. I.

The Shuttle Radar Topography Mission (SRTM) provided data for detailed topographical maps of about 80% of the Earth's land surface. SRTM consisted of single-pass C- and X-band interferometric synthetic aperture radars (INSARs). In order to utilize SRTM data in remote sensing applications the data must be calibrated and validated. This paper presents The University of Michigan's SRTM calibration and validation campaign and our results using recently acquired C-band SRTM data of our calibration sites. An array of calibration targets was deployed with the intention of determining the accuracy of INSAR-derived digital elevation maps. The array spanned one of the X-band swaths and stretched from Toledo, OH to Lansing, MI. Passive and active targets were used. The passive targets included trihedrals and tophats. The locations in latitude, longitude, and elevation of the point targets were determined using differential GPS. We also acquired U.S. Geological Survey (USGS) digital elevation models (DEMs) to use in the calibration and validation work. The SRTM data used in this study are both Principal Investigator Processor (PI) data, which are not the refined final data product, and the ground data processing system (GDPS) data, which are a more refined data product. We report that both datasets for southeastern Michigan exceed the SRTM mission specifications for absolute and relative height errors for our point targets. A more extensive analysis of the SRTM GDPS data indicates that it meets the absolute and relative accuracy requirements even for bare surface areas. In addition, we validate the PI height error files, which are used to provide a statistical characterization of the difference between the SRTM GDPS and USGS DEM heights. The statistical characterization of the GDPS-USGS difference is of interest in forest parameter retrieval algorithms.

Detection and identification of hard targets inside vegetation canopies are among the challenging problems in remote sensing. The two challenging problems are (1) computation of the field propagation through and scattering from foliage; (2) characterization of the scattering from the target illuminated by the attenuated incident field and scattered field from foliage. An accurate hybrid method is proposed to characterize the effects of scatterings from forest components and their near field interactions with the hard target. Electromagnetic (EM) scattering from vegetation canopies can be simplified in terms of problems of scattering from individual dielectric cylinders and thin dielectric disks, modeling branches and leaves, arranged in a semi-deterministic fashion. The coherent summation of all the scattering contributions is considered in order to accurately compute the total field at a given point with in the forest canopy. The total field is composed of the mean field and scattered field and the mean field is derived, using Foldy's approximation. The total field is used as the excitation to illuminate the hard target which may have complex geometry and material properties. In order to have some level of accuracy and computational efficiency, physical optics (PO) approximation, is proposed as a solution for the problem of scattering from electrically large objects. It is shown that reciprocity theorem can be effectively applied to derive the back scattered field from the induced PO currents on the target. By this, the interactions of target and foliage on both illumination and scattering are taken in to account. The challenging step in this process is to determine lit and shadowed points on the target, considering the very complex geometry of the target and very large number of the scatterers around the target, which act as a source of illumination for the target. A powerful technique is proposed to accurately and effectively calculate the induced current on the target including the effects of shadowing. This model has been applied to a simple geometry' of PEC box and the reciprocity theorem is used to estimate the back scattered field from the object.

Scattering from thin dielectric objects is a classic research topic in electromagnetics. A traditional approach is to model thin dielectrics with resistive sheets, and for several canonical geometries of resistive sheet bodies. However, for many important geometries such as disks, exact solutions are not known and only approximate solutions can be applicable to limited cases of interest. In this paper a new approximate solution is formulated based on a volumetric integral equation using Fourier transform, and it is shown that the solution is uniformly valid from low to high frequencies at all incidence angles including edge-on incidence. Validity of the solution is demonstrated through a series of comparisons with known exact solutions and a numerical solution. Method of Moment, for canonical objects such as an infinite dielectric half-plane, strip, and a circular disk for 2-D and 3-D dielectric scatterers, respectively

In this paper an uplink large array calibration technique using in-orbit targets is proposed and a forward model is developed to simulate the calibration scenario. A sensitivity study on the performance of such technique due to array phase uncertainties is conducted and the results are presented

In this paper a new statistical wave propagation (SWAP) model is introduced to model the wave propagation behavior through long distance forested environments. It divides the forest into statistically identical blocks along the wave propagation direction, By applying the existing single scattering wave theory model to one representative block of forest, it can precompute and store the statistical properties of the forest which can then be reused to compute the total power at the receiver. The computation intensity is significantly reduced while the modeling accuracy is enhanced. Three sets of simulation experiments are conducted to validate the SWAP model and the results are presented.

The IEEE Geoscience and Remote Sensing Society's Awards were presented at the IGARSS'03 banquet on Thursday, July 24 in the Hotel Dieu in Toulouse France. The GRS-S President Charles Luther, assisted by the Awards Committee Chairman Werner Wiesbeck, presented the awards. To promote excellence in research and service, each year the Geoscience and Remote Sensing Society of IEEE recognizes individuals among its members by bestowing IEEE certificates and awards.

In this paper accurate tree height retrieval for red pine and Austrian pine is demonstrated using C-band Shuttle Radar Topography Mission (SRTM) height and ancillary data. The tree height retrieval algorithm is based on modeling uniform tree stands with a single layer of randomly-oriented vegetation particles. For such scattering media, the scattering phase center (SPC) height, as measured by SRTM, is a function of tree height, incidence angle, and the extinction coefficient of the medium. The extinction coefficient for uniform tree stands is calculated as a function of tree height and density using allometric equations and a fractal tree model. The algorithm outputs tree height estimates that are significantly closer to the true tree height than the raw SRTM SPC height values obtained from the height difference between the SRTM data and the National Elevation Dataset (NED). The accuracy of the proposed algorithm is demonstrated using SRTM and TOPSAR data for 15 red pine and Austrian pine stands.

In this paper, we present a novel approach to continuous remote sensing of Earth. The proposed concept "GLORIA" drastically enhances the ability of scientists to study the Earth in a manner not possible before. The proposed system is based on a constellation of few geostationary, radar transmitter satellites and several low Earth orbiting synthetic aperture radar receiver satellites. Just as the sun is the radiation source for optical remote sensing, transmitters of microwave energy in a geostationary orbit provide the energy for radar remote sensing. Advantages of such a constellation lie in (1) a much larger number of observables, due to multi-static measurements, which significantly enhances the accuracy of retrieval algorithms, 2) the distribution of failure risk is by eliminating total system failure if a single satellite stops operating, 3) simple modular system design of small satellites through separation of transmitters and receivers (reducing weight, cost and power consumption by each satellite), and 4) flexibility in operation, that is, the receivers can be configured for different modes.

In this paper, we report on a series of foliage penetration experiments aimed at demonstrating the potential application of nadir looking, millimeter-wave radars in detecting targets under foliage cover. An algorithm is developed that classifies the radar return and isolates the radar return from hard targets.

In this paper, experimental ultra wideband radar backscatter response of a forest stand for remote sensing using applications are presented. The radar signal is a a zero-mean pulse with a duration of 1.5 ns, and rise time of 0.1 ns occupying a bandwidth 3 GHz from 0.5 GHz-3.5 GHz. The transmitter pulse amplitude exceeds 240 V in a 50 ohm transmission line giving rise to a peak power of about 1.15 kW. The transmit and receive antennas are broadband and with voltage standing-wave ratio of better than 1.2 up to 12.0 GHz. The radar is capable of transmitting both horizontal and vertical polarizations. Radar ranging of up to 180 m was achieved with a pulse repetition rate of 5 kHz. This radar was deployed to measure polarimetric backscatter from a 40-year old larch plantation stand with viewing angle varying from 50/spl deg/ to 75/spl deg/. For calibration, a corner reflector with 1 m side length was applied. Attenuation of the radar signal propagating through the canopy was extracted from the backscatter response of the the forest. Two specific features are observed from the attenuation data one having an exponential and the other having a power law dependence with distance. For the pulse scattered by the trihedral reflector imbedded in the forest, a phase diagram representing the parametric relation between the quadrature components of the receive signal is analyzed. The results obtained in this study show new possibilities for radar remote sensing of forest parameters with ultra wideband radars.

In this paper, measured attenuation and depolarization of electromagnetic fields propagating through a Larch plantation canopy in the Eastern Siberia are presented. The measurements were done with a vector antenna at 200 MHz and 1275 MHz. A spatial modulation of the received signal is observed, which is attributed to the interference among the direct, reflected, and scattered waves. Two dominant features of signal attenuation are identified. The first signal feature follows an exponential attenuation behavior while the second feature is characterized by a power-law attenuation as a function of horizontal distance from the transmitter. The latter may be attributed to a lateral wave, which propagates along the canopy-air interface shedding energy into the canopy as the signal propagates. The measured depolarization factor was found to take maximum values at locations where the field is maximum. Also, a horizontally polarized incidence wave appeared to depolarize more, as compared to vertical polarization. It is important to note that the difference in depolarization decreased at greater incidence angles, which confirms the theory that the predominant propagation mechanism is through a lateral wave. The data measured were also used for estimating an effective dielectric constant of the forest canopy as calculated from the multiple scattering theory approach.

Single-scattering theory is shown to be insufficient for the estimation of effective propagation constant in foliage at high microwave and millimetre-wave frequencies. Clusters of broad leaves and needles are treated as a unit scatterer whose ensemble forward scattering is used in Foldy's approximation to estimate attenuation rate in foliage. It is shown that single-scattering approximation overestimates forward scattering as high as 3-4 dB at 35 GHz.

In this paper, we present a comprehensive simulation of high-resolution, polarimetric synthetic aperture radar (SAR) images of forested areas. We model forest stands using realistic fractal trees over a lossy ground. The total response of the stand is calculated by coherently summing the responses of all the individual scattering components of the fractal trees, similar to the approach in Y.-C. Lin (1997, 1999). The major advantages of our simulation method are twofold: its potential high fidelity, since it employs a physics-based forest scattering model, and its ability to model high-resolution SAR response. We introduce our simulation method beginning with a description of our fractal mathematical models of trees. Next, we consider the polarimetric formulation of the received SAR signal from a forest of fractal trees. We describe methods of more efficiently calculating the received SAR signal and present a simple example of the efficiency of the simulation.

An analytical solution is presented for the elastic-wave scattering from an infinitely long, solid circular cylinder embedded in an elastic half-space. The solution utilizes the spectral (plane-wave) representation of the fields and accounts for all the multiple interactions between the interface and the buried cylinder. Compressional and shear waves are allowed in both the half-space medium and the cylinder. A buried line-source is used for excitation and several cases are considered to examine the interaction of the incident elastic waves with the buried cylinder. The solution presented here is derived in the frequency-domain but is efficient enough to provide useful time-domain results through Fourier transform techniques. Using an incident Gaussian pulse in the time-domain, simulation results demonstrate the wave components (compressional, shear, Rayleigh) on the surface of the half-space and show the effect of burial depth on the scattered wave displacement. The analytical solution is general and not limited to buried object detection but can be used in other areas, such as non-destructive evaluation of composite materials or dynamical effect studies of composites.

The Shuttle Radar Topography Mission (SRTM) provided data for detailed topographical maps of about 80% of the Earth's surface. SRTM consisted of single-pass C-and X-band interferometric synthetic aperture radars (INSARs). In order to apply SRTM data to remote sensing applications the data must be calibrated and validated. This paper presents the University of Michigan's SRTM calibration and validation campaign and our results using recently acquired C-band SRTM data of our calibration sites. A calibration array was deployed with the intention of determining the accuracy of INSAR-derived digital elevation maps. The array spanned one of the X-band swaths and stretched from Toledo, Ohio to Lansing, Michigan. Passive and active targets were used. The passive targets included trihedrals and tophats. The locations in latitude, longitude, and elevation of the point targets were determined using differential GPS. The data used in this study are "Principal Investigator Processor" data, which are not the refined final data product. However, we found the data to be of high quality. We report a 6 m to 12 m vertical height offset with a pronounced tilting trend. The average absolute offset is 9 m with a standard deviation of 2 m. This absolute height error is within the stated mission goal of 16 m, even before the final processing to refine the data. In order to calibrate the data, we remove the height offset and find that the resulting absolute height errors are at most 4.2 m in magnitude, with a standard deviation of 1.5 m.

With the advent of high-frequency radio frequency (RF) circuits and components technology, millimeter-wave (MMW) radars are being proposed for a large number of military and civilian applications. Accurate and high-resolution characterization of the polarimetric radar backscatter responses of both clutter and man-made targets at MMW frequencies is essential for the development of radar systems and optimal detection and tracking algorithms. Toward this end, a new design is developed for ultrafast, wide-band, polarimetric, instrumentation radars that operate at 35 and 95 GHz. With this new design, the complete scattering matrix of a target (magnitude and phase) can be measured over a bandwidth of 500 MHz in less than 2 /spl mu/s. In this paper, the design concepts and procedures for the construction and calibration of these radars are described. In addition, the signal processing algorithm and data-acquisition procedure used with the new radars are presented. To demonstrate the accuracy and applicability of the new radars, backscatter measurements of certain points and distributed targets are compared with their analytical radar cross section (RCS) and previously measured /spl sigma//spl deg/ values, respectively, and good agreements are shown. These systems, which can be mounted on a precision gimbal assembly that facilitates their application as high-resolution imaging radar systems, are used to determine the MMW two-way propagation loss of a corn field for different plant moisture conditions.

A full-wave solution for polarimetric scattering from a cluster of randomly oriented three-dimensional lossy dielectric structures above an impedance surface is presented to investigate the importance of multiple scattering. The problem is formulated using an integral equation in conjunction with the exact image representation of dyadic Green's function for the half-space problem. Then, the integral equation is solved for the induced equivalent polarization currents using the method of moments. The accuracy of the numerical code is verified using other existing numerical results and experimental observations. The model is then used to examine the effect of multiple scattering among a cluster of relatively short stems and is shown that multiple scattering significantly affects the cross-polarized backscatter whereas it has a moderate effect on the copolarized backscattering depending on the stem density.

A semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces is presented. Based on existing scattering models and data sets measured by polarimetric scatterometers and the JPL AirSAR, the parameters of the co-polarized phase-difference probability density function, namely the degree of correlation /spl alpha/ and the co-polarized phase-difference /spl sigmav/, in addition to the backscattering coefficients /spl sigma//sub /spl nu//spl nu///sup 0/,/spl sigma//sub hh//sup 0/ and /spl sigma//sub /spl nu/h//sup 0/, are modeled empirically in terms of the volumetric soil moisture content m/sub /spl nu// and the surface roughness parameters ks and kl, where k=2/spl pi/f/c, s is the rms height and l is the correlation length. Consequently, the ensemble-averaged differential Mueller matrix (or the differential Stokes scattering operator) is specified completely by /spl sigma//sub /spl nu//spl nu///sup 0/,/spl sigma//sub hh//sup 0/,/spl sigma//sub /spl nu/h//sup 0/,/spl alpha/, and /spl zeta/.

A polarimetric coherent electromagnetic scattering model for short branching vegetation is developed. With the realistic structures that reasonably describe the relative positions of the particles, this model is able to consider the coherent effect due to the phase difference between the scattered fields from different particles, and account for the second-order, near-field interaction between particles, to which the relative positions and orientation of the particles are essential. The model validation with measurements is also presented, and excellent agreement is obtained. The polarimetric radar backscatter measurements for soybean plants using truck-mounted scatterometers were conducted at L-band and C-band under different soil-moisture conditions. Through an extensive ground truth, the important plant and rough surface parameters such as the soil moisture and surface roughness, vegetation dielectric constant, and geometry of the soybean plants, were characterized for model verification. It is found that the second-order near-field scattering is significant at C-band for fully grown soybeans due to the high vegetation particle density, and at L-band, the contribution from the second-order near field is negligible. The coherence effect is shown to be important at L-band and to a much lesser extent at C-band. This model is then used to demonstrate its ability for estimating the physical parameters of a soybean field, including soil moisture from a polarimetric set of AIRSAR images.

The accuracy of the digital elevation model (DEM) generated by the Jet Propulsion Laboratory (JPL) TOPSAR for extracting canopy height is evaluated. For this purpose, an experiment using C-band TOPSAR at the Michigan Forest Test Site (MFTS) in Michigan's Upper Peninsula was conducted. Nearly 25 forest stands were chosen in MFTS, which included a variety of tree types, tree heights, and densities. For these stands, extensive ground data were also collected. The most important and difficult-to-characterize ground truth parameter was the forest ground level data, which is required for extracting the height of the scattering phase center from the interferometric SAR (INSAR) DEM. To accomplish this, differential Global Positioning System (GPS) measurements were done to accurately (/spl plusmn/5 cm) characterize the elevation of: (1) a grid of points over the forest floor of each stand and (2) numerous ground control points (GCPs) over unvegetated areas. Significant discrepancies between GPS and TOPSAR DEM and between the two TOPSAR DEMS of the same area were observed. The discrepancies are attributed to uncompensated aircraft roll and multipath. An algorithm is developed to remove the residual errors in roll angle using elevation data from: (1) 100-m resolution U.S. Geological Survey DEM and (2) the GPS-measured GCPs. With this: algorithm, the uncertainties are reduced to within 3 m. Still, comparison between the corrected TOPSAR DEMs shows an average periodic height discrepancy along the cross-track direction of about /spl plusmn/5 m.

A coherent scattering model for tree canopies is employed in order to characterize the sensitivity of an interferometric SAR (INSAR) response to the physical parameters of forest stands. The concept of an equivalent scatterer for a collection of scatterers within a pixel, representing the vegetation particles of tree structures, is used for identifying the scattering phase center of the pixel whose height is measured by an INSAR. Combining the recently developed coherent scattering model for tree canopies and the INSAR /spl Delta/k-radar-equivalence algorithm, accurate statistics of the scattering phase-center location of forest stands are obtained numerically for the first time. The scattering model is based on a Monte Carlo simulation of scattering from fractal-generated tree structures, and therefore is capable of preserving the absolute phase of the backscatter. The model can also account for coherent effects due to the relative position of individual scatterers and the inhomogeneous extinction experienced by a coherent wave propagating through the random collection of vegetation particles. The location of the scattering phase center and the correlation coefficient are computed using the /spl Delta/k-radar equivalence simply by simulating the backscatter response at two slightly different frequencies. The model is successfully validated using the measured data acquired by JPL TOPSAR over a selected pine stand in Raco, MI. A sensitivity analysis is performed to characterize the response of coniferous and deciduous forest stands to a multifrequency and multipolarization INSAR in order to determine an optimum system configuration for remote sensing of forest parameters.

A microwave scattering formulation is presented for grassland and other short vegetation canopies. The fact that the constituent elements of these targets can be as large as the vegetation layer make this formulation problematic. For example, a grass element may extend from the soil surface to the top of the canopy, and thus the upper portion of the element can be illuminated with far greater energy than the bottom. By modeling the long, thin elements of this type of vegetation as line dipole elements, this nonuniform illumination can be accounted for. Additionally, the stature and structure of grass plants can result in situations where the average inner-product of coherent terms are significant at lower frequencies. As a result, the backscattering coefficient cannot be modeled simply as the incoherent addition of the power from each element and scattering mechanism. To determine these coherent terms, a coherent model that considers scattered fields, and not power, is provided. This formulation is then used to provide a solution to the multiple coherent scattering terms, terms which include the correlation of the scattering between both dissimilar constituent elements and dissimilar scattering mechanisms. Finally, a major component of the grass family are cultural grasses, such as wheat and barley. This vegetation is often planted in row structures, a periodic organization that can likewise result in significant coherent scattering effects, depending on the frequency and illumination pattern. Therefore, a formulation is also provided that accounts for the unique scattering of these structures.

For pt.I see ibid., vol.38, no.1, p.339-48 (2000). The validity of a coherent, grassland scattering model is determined by comparing the model predictions with direct measurements of a representative grass canopy. A wheat field was selected as the test target, and polarimetric, multifrequency backscattering data were collected over an entire growing season, along with a complete set of ground-truth data. The L-band measured data demonstrated a strong dependence on azimuthal look direction in relation to the row direction of the wheat. The C-band measurements likewise showed an interesting backscattering response, wherein /spl sigma//sub /spl nu//spl nu///sup 0/ actually increased with incidence angle for many cases. The coherent scattering model provides backscattering data that match and predict these measured data and most of the other measured data well. The model shows that at L-band, the incoherent scattering power alone is insufficient for predicting the measured results, as the coherent terms can dominate the total scattered energy. Additionally, the model, which accounts for this nonuniform illumination of the wheat elements, demonstrates the peculiar data observed for C-band. Likewise, it is demonstrated that the fidelity used to model grass constituents (e.g., curvature) is required to match the scattering measurements accurately.

The subject of scattering of electromagnetic waves by dense media has been one of intense interest in recent years. The present paper describes polarimetric backscatter measurements made at Ku-band on layers of a dense medium under very carefully controlled circumstances. The experiments have a dual purpose: 1) to evaluate the degree to which the experimental observations are predicted by theoretical, particle-based, random media models and 2) to test a proposed hybrid model by which the scattering and extinction properties of a dense medium are characterized experimentally, allowing future modeling of the polarimetric response for any arbitrary configuration of the medium. The hybrid model assumes that first-order vector radiative transfer (RT) is a suitable theoretical structure, providing that the extinction and phase matrix components are appropriately specified; the specification is accomplished through an inversion algorithm involving polarimetric backscatter measurements. The major conclusions of the study are the following: 1) hybrid model is an adequate description of the dense medium scattering behavior; 2) conventional RT appears to give a reasonable estimate of the observed radar response, but dense medium RT gives a very low estimate; 3) phase function of the effective volume scattering element of the medium, obtained via the hybrid model, suggests a larger effective scatterer than the physical ones.

A coherent scattering model for tree canopies based on a Monte Carlo simulation of scattering from fractal-generated trees is developed and verified. In contrast to incoherent models, the present model calculates the coherent backscatter from forest canopies composed of realistic tree structures, where the relative phase information from individual scatterers is preserved. Computer generation of tree architectures faithful to the real stand is achieved by employing fractal concepts and Lindenmayer systems as well as incorporating the in situ measured data. The electromagnetic scattering problem is treated by considering the tree structure as a cluster of scatterers composed of cylinders (trunks and branches) and disks (leaves) above an arbitrary tilted plane (ground). Using the single scattering approximation, the total scattered field is obtained from the coherent addition of the individual scattering from each scatterer illuminated by a mean field. Foldy's approximation is invoked to calculate the mean field within the forest canopy that is modeled as a multilayer inhomogeneous medium. Backscatter statistics are acquired via a Monte Carlo simulation over a large number of realizations. The accuracy of the model is verified using the measured data acquired by a multifrequency and multipolarization synthetic aperture radar (SAR) [Spaceshuttle Imaging Radar-C (SIR-C)] from a maple stand at many incidence angles. A sensitivity analysis shows that the ground tilt angle and the tree structure may significantly affect the polarimetric radar response, especially at lower frequencies.

A procedure for retrieval of forest parameters is developed using the recently developed fractal-based coherent scattering model (FCSM) and a stochastic optimization algorithm. Since the fractal scattering model is computationally extensive, first a simplified empirical model with high fidelity for a desired forest stand is constructed using FCSM. Inputs to the empirical model are the influential structural and electrical parameters of the forest stand, such as the tree density, tree height, trunk diameter, branching angle, wood moisture, and soil moisture. Other finer structural features are embedded in the fractal model. The model outputs are the polarimetric and interferometric response of the forest as a function of the incidence angle. In this study, a genetic algorithm (GA) is employed as a global search routine to characterize the input parameters of a forest stand from a set of measured polarimetric/interferometric backscatter responses of the stand. The success of the inversion algorithm is demonstrated using a set of measured single-polarized interferometric synthetic aperture radar (SAR) data and several FCSM simulation results.

The application of the radar backscatter frequency correlation for classification and inversion of physical parameters of terrestrial targets is investigated. Traditionally, in radar remote sensing, the backscattering coefficients and the backscatter phase difference statistics of a distributed target are considered for estimating the biophysical parameters of interest. Because of the complex nature of random media scattering problems, however, target classification and parameter inversion algorithms are very convoluted. One obvious way of enhancing the success and accuracy of an inversion algorithm is to expand the dimension of the input vector space. Depending on the radar parameters, such as footprint (pixel) size, incidence angle, and the target attributes (physical parameters), the backscatter signal decorrelates as function of frequency. In this paper, analytical and experimental procedures are developed to establish a relationship between the complex frequency correlation function (FCF) of the backscatter and the radar and target attributes. Specifically, two classes of distributed targets are considered: 1) rough surfaces and 2) random media. Analytical expressions for the frequency correlation function are derived and it is shown that the effect of radar parameters can be expressed explicitly and thus removed from the measured correlation functions. The University of Michigan wideband polarimetric scatterometer systems are used to verify the theoretical models and inversion algorithms developed in this study.

This paper considers two specific types of experiments conducted to improve the authors' understanding of radar backscatter from snow-covered ground surfaces. The first experiment involves radar backscatter measurements at Cand X-band of artificial snow of varying depths. The relatively simple target characteristics, combined with an exhaustive ground truth effort, make the results of this experiment especially amenable to comparison with predictions based on theoretical methods for modeling volume-scattering media. It is shown that both conventional and dense-medium radiative transfer models fail to adequately explain the observed results. A direct polarimetric inversion approach is described by which the characteristics of the snow medium are extracted from the measured data. The second type of experiment examined in this study involves diurnal backscatter measurements that were made contemporaneously with detailed measurements of the snow-wetness depth profiles of the observed scene. These data are used to evaluate the capability of a recently proposed algorithm for snow wetness retrieval from polarimetric synthetic aperture radar (SAR) measurements, which has hithertofore been applied only to data from very complex and extended mountainous terrains.

Theoretical aspects of estimating vegetation parameters from SAR interferometry are presented. In conventional applications of interferometric SAR (INSAR), the phase of the interferogram is used to retrieve the location of the scattering phase center of the target. Although the location of scattering phase center for point targets can be determined very accurately, for a distributed target such as a forest canopy this is not the case. For distributed targets the phase of the interferogram is a random variable which in general is a function of the system and target attributes. To relate the statistics of the interferogram phase to the target attributes, first an equivalence relationship between the two-antenna interferometer system and an equivalent /spl Delta/k radar system is established. This equivalence relationship provides a general tool to related the frequency correlation function (FCF) of distributed targets, which can conveniently be obtained experimentally, analytically, or numerically, to the phase statistics of the interferogram. An analytical form for the p.d.f. of the interferogram phase is obtained in terms of two independent parameters: 1) /spl zeta/: mean phase and 2) /spl alpha/: degree of correlation. /spl zeta/ is proportional to the scattering phase center and n is inversely proportional to the uncertainty with which /spl zeta/ can be estimated. It is shown that /spl alpha/ is directly related to the FCF of the distributed target which in turn is a function of scattering mechanisms and system parameters. It is also shown that for a uniform closed canopy the extinction and the physical height of the canopy top can be estimated very accurately. Some analytical and numerical simulations are demonstrated.

Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (/spl epsiv//sub soil/) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of E/sub soil/. In this paper, a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of E/sub soil/ are determined from the changes in the resonant frequency and the quality factor of the resonator, respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasistatic formulation in conjunction with experimental data obtained from reference dielectric samples. Also, a simple inversion algorithm for E/sub soil/=E/sup '//sub r/-j/spl epsiv/E/sup "//sub r/ based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

The millimeter-wave (MMW) backscatter response of bare-soil was examined by conducting experimental measurements at 35 and 94 GHz using a truck-mounted polarimetric scatterometer and by developing appropriate models to relate the backscattering coefficient to the soil's surface and volume properties. The experimental measurements were conducted for three soil surfaces with different roughnesses under both dry and wet conditions. The experimental measurements indicate that in general the backscattering coefficient is comprised of a surface scattering component /spl sigma//sup s/ and a volume scattering component /spl sigma//sup v/. For wet soil conditions, the backscatter is dominated by surface scattering, while for dry conditions both surface and volume scattering are significant, particularly at 94 GHz. Because theoretical surface scattering models were found incapable of predicting the measured backscatter, a semiempirical surface scattering model was developed that relates the surface scattering component of the total backscatter to the roughness parameter ks, where k=2/spl pi///spl lambda/ and s is the rms height, and the dielectric constant of the soil surface. Volume scattering was modeled using radiative transfer theory with the packed soil particles acting as the host material and the air voids as the scattering particles. The combined contribution of surface and volume scattering was found to provide good agreement between the model calculations and the experimental observations.

An efficient numerical solution for the scattering problem of inhomogeneous dielectric rough surfaces is presented. The inhomogeneous dielectric random surface represents a bare soil surface and is considered to be comprised of a large number of randomly positioned dielectric humps of different sizes, shapes, and dielectric constants above an impedance surface. Clods with nonuniform moisture content and rocks are modeled by inhomogeneous dielectric humps and the underlying smooth wet soil surface is modeled by an impedance surface. In this technique, an efficient numerical solution for the constituent dielectric humps over an impedance surface is obtained using Green's function derived by the exact image theory in conjunction with the method of moments. The scattered field from a sample of the rough surface is obtained by summing the scattered fields from all the individual humps of the surface coherently ignoring the effect of multiple scattering between the humps. The statistical behavior of the scattering coefficient /spl sigma//spl deg/ is obtained from the calculation of scattered fields of many different realizations of the surface. Numerical results are presented for several different roughnesses and dielectric constants of the random surfaces. The numerical technique is verified by comparing the numerical solution with the solution based on the small perturbation method and the physical optics model for homogeneous rough surfaces. This technique can be used to study the behavior of scattering coefficient and phase difference statistics of rough soil surfaces for which no analytical solution exists.

Radar backscatter experiments were conducted at 35 and 95 GHz to measure the response of snow-covered ground to snow depth, liquid water content, and ice crystal size. The measurements included observations over a wide angular range extending between normal incidence and 60/spl deg/ for all linear polarization combinations. A numerical radiative transfer model was developed and adapted to fit the experimental observations. Next, the radiative transfer model was exercised over a wide range of conditions and the generated data were used to develop relatively simple semi-empirical expressions that relate the backscattering coefficient (for each linear polarization) to incidence angle, snow depth, crystal size, and liquid water content.

A three-step process is presented for estimation of forest biophysical properties from orbital polarimetric SAR data. Simple direct retrieval of total aboveground biomass is shown to be ill-posed unless the effects of forest structure are explicitly taken into account. The process first involves classification by (1) using SAR data to classify terrain on the basis of structural categories or (2) a priori classification of vegetation type on some other basis. Next, polarimetric SAR data at L- and C-bands are used to estimate basal area, height and dry crown biomass for forested areas. The estimation algorithms are empirically determined and are specific to each structural class. The last step uses a simple biophysical model to combine the estimates of basal area and height with ancillary information on trunk taper factor and wood density to estimate trunk biomass. Total biomass is estimated as the sum of crown and trunk biomass. The methodology is tested using SIR-C data obtained from the Raco Supersite in Northern Michigan on Apr. 15, 1994. This site is located at the ecotone between the boreal forest and northern temperate forests, and includes forest communities common to both. The results show that for the forest communities examined, biophysical attributes can be estimated with relatively small rms errors: (1) height (0-23 m) with rms error of 2.4 m, (2) basal area (0-72 m/sup 2//ha) with rms error of 3.5 m/sup 2//ha, (3) dry trunk biomass (0-19 kg/m/sup 2/) with rms error of 1.1 kg/m/sup 2/, (4) dry crown biomass (0-6 kg/m/sup 2/) with rms error of 0.5 kg/m/sup 2/, and (5) total aboveground biomass (0-25 kg/m/sup 2/) with rms error of 1.4 kg/m/sup 2/. The addition of X-SAR data to SIR-C was found to yield substantial further improvement in estimates of crown biomass in particular. However, due to a small sample size resulting from antenna misalignment between SIR-C and X-SAR, the statistical significance of this improvement cannot be reliably established until further data are analyzed. Finally, the results reported are for a small subset of the data acquired by SIR-C/X-SAR.>

The SIR-C/X-SAR imaging radar took its first flight on the Space Shuttle Endeavour in April 1994 and flew for a second time in October 1994. This multifrequency radar has fully polarimetric capability at L- and C-band, and a single polarization at X-band (X-SAR). The Endeavour missions were designated the Space Radar Laboratory-1 (SRL-1) and -2 (SRL-2). Calibration of polarimetric L- and C-band data for all the different modes SIR-C offers is an especially complicated problem. The solution involves extensive analysis of pre-flight test data to come up with a model of the system, analysis of in-flight test data to determine the antenna pattern and gains of the system during operation, and analysis of data from over fourteen calibration sites distributed around the SIR-C/X-SAR orbit track. The SRL missions were the first time a multifrequency polarimetric imaging radar employing a phased array antenna has been flown in space. Calibration of SIR-C data products involved some unique technical problems given the complexity of the radar system. In this paper, the approach adopted for calibration of SIR-C data is described and the calibration performance of the data products is presented.>

An efficient and realistic electromagnetic scattering model for a tree trunk above a ground plane is presented. The trunk is modeled as a finite-length stratified dielectric cylinder with a corrugated bark layer. The ground is considered to be a smooth homogeneous dielectric with an arbitrary slope. The bistatic scattering response of the cylinder is obtained by invoking two approximations. In the microwave region, the height of the tree trunks are usually much larger than the wavelength. Therefore the interior fields in a finite length cylinder representing a tree trunk can be approximated with those of an infinite cylinder with the same physical and electrical radial characteristics. Also an approximate image theory is used to account for the presence of the dielectric ground plane which simply introduces an image excitation wave and an image scattered field. An asymptotic solution based on the physical optics approximation is derived which provides a fast algorithm with excellent accuracy when the radii of the tree trunks are large compared to the wavelength. The effect of a bark layer is also taken into account by simply replacing the bark layer with an anisotropic layer. It is shown that the corrugated layer acts as an impedance transformer which may significantly decrease the backscattering radar cross section depending on the corrugation parameters. It is also shown that for a tilted ground plane a significant cross-polarized backscattered signal is generated while the co-polarized backscattered signal is reduced.>

In preparation for the Shuttle Imaging Radar-C/XSAR (SIR-C/XSAR) flights, the University of Michigan has been involved in the development of calibration procedures and precision calibration devices to quantify the complex radar images with an accuracy of 0.5 dB in magnitude and 5 degrees in phase. In this paper, the preliminary results of the SIR-C calibration and a summary of the University of Michigan's activity in the Raco calibration super-site is presented. In this calibration campaign an array of point calibration targets including trihedral corner reflectors and polarimetric active radar calibrators (PARCs) in addition to a uniform distributed target were used for characterizing the radiometric calibration constant and the distortion parameters of the C-band SAR. Two different calibration methods, one based on the application of point targets and the other based on the application of the distributed target, are used to calibrate the SIR-C data and the results are compared with calibrated images provided by JPL. The distributed target used in this experiment was a field of grass, sometimes covered with snow, whose differential Mueller matrix was measured immediately after the SIR-C overpass using The University of Michigan polarimetric scatterometer systems. The scatterometers were calibrated against a precision metallic sphere and measured 100 independent spatial samples for characterizing the differential Mueller matrix of the distributed target to achieve the desired calibration accuracy. The L-band SAR has not yet been adequately calibrated for inclusion here.>

The amount of water present in liquid form in a snowpack exercises a strong influence on the radar and radiometric responses of snow. Conventional techniques for measuring the liquid water content m/sub /spl upsi// suffer from various shortcomings, which include poor accuracy, long analysis time, poor spatial resolution, and/or cumbersome and inconvenient procedures. This paper describes the development of a hand-held electromagnetic sensor for quick and easy determination of snow liquid water content and density. A novel design of this probe affords several important advantages over existing similar sensors. Among these are improved spatial resolution and accuracy, and reduced sensitivity to interference by objects or media outside the sample volume of the sensor. The sensor actually measures the complex dielectric constant of the snow medium, and the water content and density must be obtained through the use of empirical or semi-empirical relations. To test the suitability of existing models and allow the development of new models, the snow probe was tested against the freezing calorimeter and gravimetric density determinations. From these comparisons, valid models were selected or developed. Based on the use of these models, the following specifications were established for the snow probe: 1) liquid water content measurement accuracy=/spl plusmn/0.66% in the wetness range from 0 to 10% by volume and 2) wet snow density measurement accuracy=/spl plusmn/0.05 g/cm/sup 3/ in the density range from 0.1 to 0.6 g/cm/sup 3/.>

In preparation for the flight of the Shuttle Imaging Radar-C (SIR-C) on board the Space Shuttle in the spring of 1994, a level-1 automatic classifier was developed on the basis of polarimetric SAR images acquired by the JPL AirSAR system. The classifier uses L- and C-Band polarimetric SAR measurements of the imaged scene to classify individual pixels into one of four categories: tall vegetation (trees), short vegetation, urban, or bare surface, with the last category encompassing water surfaces, bare soil surfaces, and concrete or asphalt-covered surfaces. The classifier design uses knowledge of the nature of radar backscattering from surfaces and volumes to construct appropriate discriminators in a sequential format. The classifier, which was developed using training areas in a test site in Northern Michigan, was tested against independent test areas in the same test site and in another site imaged three months earlier. Among all cases and all categories, the classification accuracy ranged between 91% and 100%.>

The retrieval of scene parameters from polarimetric radar data using an iterative inversion approach is considered. The theoretical development of a general, model-based iterative algorithm for inversion of polarimetric radar data is presented. Factors relevant to its implementation, such as sensor configuration, algorithm optimization and computational structure are discussed. The algorithm is applied to the specific problem of inverting the vector radiative transfer model for a simplified, representative vegetation canopy consisting of vertical trunks, leaves, and a rough ground surface. The results of this inversion are in excellent agreement with simulated data generated using the radiative transfer model. The convergence properties of the algorithm are evaluated, and it is found that successful convergence is achieved in about 90% to 95% of the cases tested for the implementation used in this work. An error analysis is presented which considers the effect of both systematic and measurement derived errors. Typical error bounds for the current application are approximately /spl plusmn/3%, allowing for /spl plusmn/0.5 dB accuracy in the measured radar data.>

Existing methods for external calibration of polarimetric synthetic aperture radars (SAR) are all based on point targets with known scattering matrices. The quantity of interest in radar measurement of distributed targets is the backscattering coefficient, which is different from the radar cross section (RCS) formulated for point targets. Therefore, in order to infer the backscattering cross section of a distributed target from a point target rigorously, the polarimetric ambiguity function of the SAR (unknown) is needed for the computation of the effective illumination area. In existing methods the illumination area is approximated by the area of a pixel. The second problem is the uncertainty in the RCS of point calibration targets. The large physical size of the point targets and their interaction with the background produce uncertainties in the measurement of the calibration targets. The third problem with existing methods arises from the application of the calibration algorithm to individual pixels. The measured response of a distributed target by a SAR is the convolution of the actual radar reflectivity of the target with the ambiguity function of the SAR. Thus, the statistics derived from individual pixels is influenced by the ambiguity function and the measurement becomes system dependent. In this paper a calibration algorithm is proposed that circumvents all of the mentioned problems. It is shown that the radar distortion parameters and effective illumination area can be obtained from a homogeneous distributed target with a known differential Mueller matrix. The distortion parameters are then used in an algorithm to provide the calibrated differential Mueller matrix for the other homogeneous targets in the image. This algorithm is tested for the JPL L- and C-band SAR using four different distributed targets measured with polarimetric scatterometers.>

When point calibration targets are used to calibrate a SAR image, the calibration accuracy is governed by two major factors. The first factor stems from the stringent requirement on the radar cross section (RCS) of the point calibration target. To reduce the effect of radar return from the background, the RCS of a point calibration target must be much larger than that of the background. Calibration targets with large RCS require large physical dimensions for passive targets or high amplifier gain for active targets, which in practice leads to uncertainty in the nominal RCS of the targets. The second factor is related to the fact that point calibration targets are used to develop a calibration algorithm which is applied to distributed targets. To this end, accurate knowledge of the impulse response (ambiguity function) of the SAR system is required. To evaluate the accuracy of such a calibration process, a cross-calibration experiment was conducted at a test site near Pellston, MI, using the JPL aircraft SAR and the University of Michigan truck-mounted polarimetric scatterometer. Five different types of distributed surfaces, all in the same area, were chosen: three of these were bare surfaces with varying roughnesses, and the other two were covered with vegetation. Trihedral corner reflectors were used for calibrating the aircraft SAR, and the UM scatterometer was calibrated using a metallic sphere. The scatterometer data were collected at L and C bands immediately after the aircraft flew over the test site. This paper presents results of the cross calibration between the polarimetric SAR and ground-based polarimetric scatterometer measurements at L and C bands. Comparison of the data measured by the two radar systems shows that SAR calibration with trihedrals may lead to unreliable results. A distributed-target calibration technique is introduced and applied to the data with good results.>

The EM scattering solution for a grass blade with complex cross-section geometry is considered. It was previously shown that the scattering solution for such problems, in the form of a polarizability tensor, can be obtained using the low-frequency approximation in conjunction with the method of moments. In addition, that study showed that the relationship between the polarizability tensor of a dielectric cylinder and its dielectric constant can be approximated by a simple algebraic expression. The results of that study are used to show that this algebraic approximation is valid also for cylinders with cross sections the shape of grass blades, providing that proper values are selected for each of three constants appearing in the expression. These constants are dependent on cylinder shape, and if the relationship between the constants and the three parameters describing a grass blade shape can be determined, an algebraic approximation relating polarizability tensor to blade shape, as well as dielectric constant, can be formed. This algebraic approximation can replace the cumbersome method of moments model. The moment method model is therefore used to generate a small but representative set of polarizability tensor data over the range of values commonly observed in nature. A conjugate gradient method is then implemented to correctly determine the three constants of the algebraic approximation for each blade shape. A third-order polynomial fit to the data is then determined for each constant, thus providing a complete analytic replacement to the numerical (moment method) scattering model.>

The authors examine an image obtained by the C-band VV-polarized ERS-1 SAR with respect to potential land applications. A scene obtained near noon on Aug. 15, 1991, along the US-Canadian border near Sault Ste. Marie is calibrated relative to an array of trihedral corner reflectors and active radar calibrators distributed across the swath. Extensive contemporaneous ground observations of forest stands are used to predict sigma degrees at the time of the SAR overpass using a first-order vector radiative transfer model (MIMICS). These predictions generally agree with the calibrated ERS-1 data to within 1 dB. It is demonstrated that the dynamic range of sigma degrees is sufficient to perform limited discrimination of various forest and grassland communities even for a single-date observation. Furthermore, it is demonstrated that retrieval of near-surface soil moisture is feasible for grass-covered soils when plant biomass is less than 1 tonne/ha.>

Polarimetric radar measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10 degrees to 70 degrees . Using a laser profiler and dielectric probes, a complete and accurate set of ground truth data was collected for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. Based on knowledge of the scattering behavior in limiting cases and the experimental observations, an empirical model was developed for sigma degrees /sub hh/, sigma degrees /sub vv/, and sigma degrees /sub hv/ in terms of ks (where k=2 pi / lambda is the wave number and s is the rms height) and the relative dielectric constant of the soil surface. The model, which was found to yield very good agreement with the backscattering measurements of the present study as well as with measurements reported in other investigations, was used to develop an inversion technique for predicting the rms height of the surface and its moisture content from multipolarized radar observations.>

Calibration using point targets is discussed. The fourport network calibration technique is used to describe the radar error model. The processor ambiguity function and the radar distortion matrices are combined to form a generalized polarimetric ambiguity function. The polarimetric ambiguity function of the SAR is found using a single point target, namely a trihedral corner reflector. Based on the resultant polarimetric ambiguity function, an estimate for the backscattering coefficient of the terrain is found using a modified version of the single target calibration technique (STCT). A radar image recorded by the JPL aircraft SAR, which includes a variety of point targets, is used for verification of the new calibration method. The calibrated responses of the point targets are compared both with theory and responses based on the POLCAL technique.>