The European Space Agency's (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission's primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite's advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.

This paper introduces a new waveform design approach called COSMIC (Connectivity-Oriented Sensing Method for Imaging and Communication). The method enables the creation of radio images of the environment by applying an extended orthogonality condition to the waveforms. Unlike conventional systems that use time, frequency, or space multiplexing, COSMIC achieves orthogonality through algebraic precoding of the signals from all antennas. Additionally, COSMIC takes advantage of the fact that the imaging field of view is much smaller than the length of the transmitted signals, allowing the waveforms to carry communication data without disrupting the sensing function. Simulations show that COSMIC waveforms enable precise environmental imaging while maintaining good communication performance in terms of error rates.

Sensing in non-line-of-sight (NLOS) is a well-known issue that limits the range of radar-like sensors. Existing approaches rely on either metallic mirrors, that only work under specular reflection, or dynamically-reconfigurable metasurfaces that steer the signal to cover a desired area in NLOS, with the drawback of cost and control signaling. This paper proposes a novel vehicular sensing method, here referred as Stroboscopic Sensing, where a moving source images a desired region of interest (ROI) in NLOS leveraging on source beam sweeping over a sufficiently large portion of a reflection plane, passively pre-configured as a periodic angular deflecting function to illuminate the ROI. Consequently, the source is able to cover the ROI and enhance the spatial resolution of the image, thanks to multiple diverse observation angles of ROI. In the context of vehicular sensing systems, our method allows a moving vehicle to perceive its surroundings beyond obstacles, improving situational awareness. Remarkably, the proposed method achieves near-field imaging with a sequence of far-field acquisitions, thus limiting the implementation complexity. We detail the system design criteria and trade-offs, demonstrating the remarkable benefits of such sensing method, where a possibly moving source can observe a ROI through multiple points of view as if it were static.

In this paper we present a first demonstration of spaceborne L-band SAR Tomography over a forested scenario. To this aim, we process a SAOCOM stack of nine acquisitions with across-track baselines theoretically achieving a vertical resolution around 22 m. To obtain a correct TomoSAR imaging, we phase calibrate the stack by properly accounting for forest volumetric structure, which drives the choice of calibrating with smaller baselines. Finally, we ground steer calibrated TomoSAR to achieve a consistent reconstruction of forest structure above ground and derive a forest height map. Comparison with reference canopy height gives a very good overall agreement, proving the effectiveness of our approach and making the experiment an interesting test-bed in view of future long-wavelength SAR missions.

Exploring vertical forest structures worldwide via remote sensing faces challenges. Recent technologies like waveform light detection and ranging (LiDAR) from NASA’s global ecosystem dynamics investigation (GEDI) and SAR tomography (TomoSAR) from future European Space Agency (ESA) BIOMASS offer promising solutions. This article assesses the performance of spaceborne GEDI and TomoSAR airborne data from an ESA’s TomoSense campaign to highlight the important role of GEDI measurements in BIOMASS algorithm training and establishing precise site-specific processing parameters. Our study in Germany’s Eifel National Park delves into the precision of GEDI and P-band TomoSAR in measuring surface [digital terrain model (DTM)] and vegetation [canopy height model (CHM)] heights. Results demonstrate that GEDI and P-band TomoSAR offer high-resolution and precise surface and vegetation heights and vertical profile measurements. While GEDI relative height (RH) at 98% (RH98) was previously recommended for tropical forests, our findings advocate for RH85 as the optimal metric for temperate forests. The research supports improving the accuracy of both DTM and CHM utilizing GEDI beams with full-power lasers coupled with high sensitivity and signal-to-noise ratio (SNR). Ground elevation measurements are more accurate than canopy height estimates for temperate forests, with DTM RMSE about 2 m and CHM RMSE about 3 m for GEDI and TomoSAR measurements. By analyzing the vertical structure of monthly GEDI data, we note a 1-m shift in the volume peak between GEDI’s leaf-on and leaf-off periods. At the same time, TomoSAR consistently exhibits a lower volume peak by about 2 m compared to GEDI during leaf-on seasons. In conclusion, our research underscores the complementary roles of TomoSAR and GEDI in accurately mapping diverse forest types, thereby bolstering the effectiveness of the BIOMASS mission.

The vast accessibility of Synthetic Aperture Radar (SAR) images through online portals has propelled the research across various fields. This widespread use and easy availability have unfortunately made SAR data susceptible to malicious alterations, such as local editing applied to the images for inserting or covering the presence of sensitive targets. To contrast malicious manipulations, in the last years the forensic community has begun to dig into the SAR manipulation issue, proposing detectors that effectively localize the tampering traces in amplitude images. Nonetheless, in this paper we demonstrate that an expert practitioner can exploit the complex nature of SAR data to obscure any signs of manipulation within a locally altered amplitude image. We refer to this approach as a counter-forensic attack. To achieve the concealment of manipulation traces, the attacker can simulate a re-acquisition of the manipulated scene by the SAR system that initially generated the pristine image. In doing so, the attacker can obscure any evidence of manipulation, making it appear as if the image was legitimately produced by the system. This attack has unique features that make it both highly generalizable and relatively easy to apply. First, it is a black-box attack, meaning it is not designed to deceive a specific forensic detector. Furthermore, it does not require a training phase and is not based on adversarial operations. We assess the effectiveness of the proposed counter-forensic approach across diverse scenarios, examining various manipulation operations. The obtained results indicate that our devised attack successfully eliminates traces of manipulation, deceiving even the most advanced forensic detectors.

This paper illustrates the potential of an Integrated Sensing and Communication (ISAC) system, operating in the sub-6 GHz frequency range, for Synthetic Aperture Radar (SAR) imaging via an Unmanned Aerial Vehicle (UAV) employed as an aerial base station. The primary aim is to validate the system's ability to generate SAR imagery within the confines of modern communication standards, including considerations like power limits, carrier frequency, bandwidth, and other relevant parameters. The paper presents two methods for processing the signal reflected by the scene. Additionally, we analyze two key performance indicators for their respective fields, the Noise Equivalent Sigma Zero (NESZ) and the Bit Error Rate (BER), using the QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa), demonstrating the system's capability to image buried targets in challenging scenarios. The paper shows simulated Impulse Response Functions (IRF) as possible pulse compression techniques under different assumptions. An experimental campaign is conducted to validate the proposed setup by producing a SAR image of the environment captured using a UAV flying with a Software-Defined Radio (SDR) as a payload.

In this work we present a first spaceborne L-band forest SAR Tomography (TomoSAR). We process a stack of 9 real SAOCOM acquisitions over Amazonas, a scenario mostly consisting of tropical rainforest with average tree height of about 25 m to 35 m. We phase calibrate the stack with Phase Linking algorithm, in order to obtain a consistent reconstruction of forest over terrain and compare TomoSAR results with different spectral estimators. We achieve good results with MUSIC spectral estimator, coping with spatial and temporal baselines and compare the upper TomoSAR envelope with LiDAR forest height. The overall agreement is quite good, confirming the effectiveness of our approach.

This paper studies the potential of X-band space borne SAR tomography for characterizing the structure of snow packs. The proposed solution is based on a constellation of 4 or 5 small satellites operated in a specific MIMO-FDM configuration, whose geometrical and spectral features are optimized so as to reach vertical resolution and ambiguity figures equivalent to 25 monostatic sensors. Estimation performance bounds, computed for specific scenarios, show that this concept is able to accurately capture the internal structure of shallow or deep snow-packs from a single measurement and to unambiguously estimate Snow Water Equivalent using two observations, with a very high accuracy and without assumptions on the structure or thickness of the measured cover.

Our study highlights the important role of GEDI measurements in BIOMASS algorithm training and the establishment of precise site-specific processing parameters. Combining GEDI measurements at sparse coordinates and SAR tomography (TomoSAR) estimates enables the creation of detailed canopy height maps (CHM). While relative height (RH) at 98% (RH98) was previously recommended for tropical forests, our findings advocate for RH85 as the optimal metric for temperate forests. Emphasis is placed on selecting shots with over 90% sensitivity for ground return detection and GEDI beams equipped with full-power lasers. Additionally, we show the GEDI profile data’s unique capacity to investigate annual changes, revealing significant volume contributions during leaf-on periods and increased ground importance during leaf-off seasons.

This paper aims to showcase the potential of an Integrated Communication and Sensing (ISAC) system, operating within the sub-6 GHz frequency range, for Synthetic Aperture Radar (SAR) imaging through an Unmanned Aerial Vehicle (UAV). Our primary goal is to validate the system’s ability to generate SAR imagery under practical constraints dictated by contemporary communication standards, including factors like maximum transmitted power, carrier frequency, occupied bandwidth, Pulse Repetition Frequency, and the number of sub-carriers. The paper provides a detailed description of the Orthogonal Frequency Division Multiplexing (OFDM) signal transmitted by the base station. We compare two methods for range-compressing the signal backscattered by the scene and analyze the Noise Equivalent Sigma Zero (NESZ) under classical line-of-sight conditions and in challenging environments, demonstrating the system’s capability to detect targets under snow. It also showcases simulated Impulse Response Functions (IRF) under various assumptions, as well as real SAR images of the environment obtained using a UAV with a software-defined radar (SDR) integrated as a payload.

This work provides the signal processing workflow to focus Unmanned Aerial Vehicles (UAV) Synthetic Aperture Radar (SAR) images with partially unknown or corrupted trajectories. The processing chain is divided into two modular blocks. The former involves a novel and low-complexity autofocusing technique. This method applies geometric corrections directly to the nominal trajectory, getting rid of the assumption of a constant phase correction, that does not hold with highly variable squint and off-nadir angles, as for the case of UAV-borne SAR. The latter modular block concerns a Fast Factorised Back Projection (FFBP) based focusing scheme. In particular, for a given scenario the processor computes a priori the computational burden in order to define the most appropriate reference system and the degree of hierarchical merging to focus the scene at the minimum computational cost. In light of this, the proposed focusing algorithm is able to deal with a complex trajectory typical of UAVs and to focus a large image at high resolution. Two scenarios are considered. The former is a UAV-borne SAR experiment with a small aperture, a long range, and a wide area covered by a large antenna aperture. The latter is a proper UAV-borne SAR stripmap scenario. Here, the proposed focusing scheme performs better than the traditional FFBP. Finally, the results are supported by a numerical simulation to prove the effectiveness of the whole processing scheme.

Bistatic Correlation Tomography is an innovative radar technique capable of retrieving the vertical structure of the target. By combining pairs of simultaneous SAR images collected in multiple bistatic passes, the distribution in elevation of the backscattered power can be reconstructed. This processing technique is particularly interesting for the observation of natural targets because it is not sensitive to temporal decorrelation. For this reason, we consider its application to forestry. The goal of this work is twofold: In the first place, an analytical model for assessing the performances of Correlation Tomography is derived and validated through a numerical simulation. Then, a procedure for recovering tomographic products in the presence of very irregular baselines is proposed. This procedure is then tested using real data from the TomoSense campaign.

This paper investigates the use of the Phase Histogram (PH) technique for the remote sensing of forested areas using Synthetic Aperture Radar (SAR) data. The PH technique assigns each pixel in a SAR interferogram to a specific height bin based on the value of the corresponding interferometric phase, thus allowing for the estimation of the forest vertical structure by accumulating pixels magnitudes within a given spatial window. In this paper, we first analyze the formation of phase histograms from a theoretical perspective, explicitly considering the role played by phase dispersion as a function of the number of targets within the SAR resolution cell. Theoretical developments are followed by further experimental analyses of L-Band data from the ESA campaign TomoSense, flown at the Eifel National Park, Germany, in 2020/2021. Theoretical and experimental results indicate that the applicability of the PH technique is subject to the assumption that Radar returns are determined by the presence of a dominant scatterer in each SAR resolution cell, in which case the phase histogram can successfully represent the forest electromagnetic structure. This leads to the conclusion that the PH technique is best suited for the analysis of high-frequency and/or highresolution data, in which conditions PH may perform satisfactorily based on single interferograms.

Coherent multistatic radio imaging represents a pivotal opportunity for forthcoming wireless networks, which involves distributed nodes cooperating to achieve accurate sensing resolution and robustness. This paper delves into cooperative coherent imaging for vehicular radar networks. Herein, multiple radar-equipped vehicles cooperate to improve collective sensing capabilities and address the fundamental issue of distinguishing weak targets in close proximity to strong ones, a critical challenge for vulnerable road users’ protection. We prove the significant benefits of cooperative coherent imaging in the considered automotive scenario in terms of both probability of correct detection, evaluated considering several system parameters, as well as resolution capabilities, showcased by a dedicated experimental campaign wherein the collaboration between two vehicles enables the detection of the legs of a pedestrian close to a parked car. Moreover, as coherent processing of several sensors’ data requires very tight accuracy on clock synchronization and sensor’s positioning—referred to as phase synchronization—(such that to predict sensor-target distances up to a fraction of the carrier wavelength), we present a general three-step cooperative multistatic phase synchronization procedure, detailing the required information exchange among vehicles in the specific automotive radar context and assessing its feasibility and performance by hybrid Cramér-Rao bound.

Tomographic synthetic aperture radar (TomoSAR) is a promising technique for the estimation of forest above-ground biomass (AGB), but knowledge gaps still remain concerning the effects of forest type and ground topography. This article presents new results at P- and L-bands based on data acquired during the TomoSense campaign. The study area is a temperate forest, predominantly beech and spruce, with ground slopes ranging up to 40°. Analysis of vertical reflectivity profiles shows distinct differences for spruce and beech. Three AGB retrieval methods are analyzed, i.e., total vertical backscatter$I_{\text {tot}}$, canopy backscatter from a height layer$I_{c}$, and the ratio$I_{\text {cr}} = I_{c}/I_{\text {tot}}$. All three methods show sensitivity to AGB for spruce, whereas for beech, this is only true for the two latter methods. For the P-band, a significant ground slope effect is observed, while less so for the L-band. The highest$R^{2}$is obtained for spruce with HV polarization,$I_{c}$and ground slopes less than 10°, i.e.,$R^{2} = 0.86$and RMSE =15.6% for P-band and$R^{2} = 0.75$and RMSE =12.5% for L-band. Corresponding results by including all forest types are$R^{2} = 0.77$and RMSE =11.4% for P-band and$R^{2} = 0.54$and RMSE =12.0% for the L-band. Moreover, the performance of using$I_{\text {cr}}$is similar to that of$I_{c}$. The ratio$I_{\text {cr}}$can be determined without absolute radiometric calibration which relaxes system requirements. This article reinforces the potential of TomoSAR for forest AGB estimation and draws attention to important effects of tree species and ground slope.

This work investigates a new concept to finely resolve the vertical structure of natural media, like snow, ice, vegetation, by using a formation of spaceborne Synthetic Aperture Radars (SAR) mounted onboard different satellites. The formation is assumed to operate in Multiple Input Multiple Output (MIMO) mode by implementing a Frequency Division Multiplexing (FDM) access scheme, where all satellites transmit simultaneously on different frequency bands and receive the echoes scattered by the Earth’s surface in all transmitted bands. In so-doing, a formation onNsatellites is used to produceN2SAR images. By the principle of Diffraction Tomography, each of these images represents a distinct set of wavenumbers, i.e. a distinct region of the spatial spectrum of the observed scene. The vertical separation between any two sets of wavenumbers defines the interferometric differential wavenumber, which determines the sensitivity of that particular pair to the vertial structure of the observed scene. Fine vertical resolution is achieved by developing a novel approach to set the satellite positions in such a way that the resulting interferometric differential wavenumbers form an almost uniformly-spaced array of maximum length under the constraint of a given height of ambiguity and interferometric coherence magnitude. As a result, we show two examples where formations of 4 or 5 satellites are deployed to provide the equivalent of 17 and 26 monostatic acquisitions, respectively. Such figures are comparable to the best airborne and ground-based systems available as of today, and indicate the concrete possibility to image the vertical structure of natural targets from space at fine resolution. The concept here developed to deploy the formation is referred to as Minimum Redundancy Wavenumber Illumination (MRWI), as it is shown to be a generalization to distributed targets of the principle of Minimum Redundancy Virtual Array (MRVA) used in array theory. The analysis is supported by results from synthetic data generated by numerical simulations.

This article evaluates the recently introduced phase histogram (PH) technique for estimating forest height and vertical structure using theoretical modeling and experimental synthetic aperture radar (SAR) data. The PH technique assigns each pixel in an SAR interferogram to a specific height bin based on the value of the corresponding interferometric phase, thus allowing for the estimation of the forest’s vertical structure by accumulating pixels magnitudes within a given spatial window. This approach is radically different from the one employed by SAR tomography (TomoSAR), which allows for direct imaging of the 3-D structure of the vegetation by jointly focusing on SAR data from multiple trajectories. Importantly, PHs can be built using as few as two images (a single interferogram), whereas TomoSAR is well-known to perform best when many images area available. Accordingly, the main question we intend to address in this article is to what extent and in which conditions single-baseline PHs can be used as a surrogate of TomoSAR (in the absence of multibaseline data). Experimental analyses are conducted using L-band tomographic SAR data from the ESA campaign TomoSense, flown in 2020 at Eifel Park in North West Germany. TomoSense data include 30 + 30 monostatic overpasses acquired along two opposite flight headings, and are complemented by airborne, terrestrial, and unmanned aerial vehicle (UAV) Lidar surveys. Lidar data are used to generate a forest canopy height model (CHM) and vertical profiles of leaf area density (LAD), taken as the main reference in the evaluation of PHs. Multibaseline tomographic data are produced and investigated to assess the actual sensitivity of radar data to forest structure at this site, as well as to provide indications about the performance of a radar instrument when multiple baselines are available. Experimental results indicate that the PH technique can only loosely approximate the vertical structure produced by TomoSAR. Still, it can produce a reasonably good estimate of forest height. In particular, TomoSAR and the PH technique are observed to have an average root mean square error (RMSE) with respect to Lidar estimate of 2.8 and 4.45 m in North-West heading data, and 1.84 and 5.46 m in South-East heading data, respectively. The observed results are interpreted in light of a simple physical model to characterize PHs depending on the number of scatterers within the SAR resolution cell, on which basis we derive analytical expressions to predict height dispersion in PHs. The proposed model indicates that the concept of PH is inherently based on the assumption of a single dominant scatterer within any single SAR resolution cell. If this is not the case, PHs produce an intrinsic dispersion that does not represent the actual vertical distribution of scatterers within the vegetation. Consistently, we conclude that the PH technique is inherently best suited for the analysis of high- or very-high resolution data, which suggests its use in the context of higher frequency SAR missions (e.g., Tandem-X) and when there are few acquisitions available.

BIOMASS is new ESA Earth Explorer, scheduled for launch in 2024. It will be the first P-band spaceborne Synthetic Aperture Radar (SAR), featuring full polarimetry, repeat pass interferometry and tomography. Its main objective is global routine monitoring of forested areas, its secondary objectives include exploration of glacier dynamics, subsurface geology and sub-canopy terrain topography. In order to correctly retrieve information, interferometric calibration has to address main disturbances affecting repeat pass P-band SAR: ionosphere, baseline errors and troposphere. In this paper we present the scientific design of BIOMASS interferometric calibration processor, detailing the state-of-the-art correction steps implemented. Some preliminary results obtained by processing simulated acquisitions are illustrated to motivate the proposed techniques.

This paper tackles two open problems concerning automotive Synthetic Aperture Radar (SAR): whether it is possible to develop a fast and efficient focusing routine and assess the effect of multipath on MIMO-SAR images. First, we present a processing technique that enables real-time imaging of the scene under observation. The idea is that the SAR image is already present in the Range-Angle-Velocity (RAV) data cube and must be extracted with a simple 3D interpolation. Unlike standard Doppler beam sharpening techniques, this processor is accurate since it handles range migration and phase curvature. For what concerns the multipath, instead, we introduce a simple yet effective approach to mitigate this issue, which significantly improves the robustness of SAR systems concerning multipath. To showcase the capabilities and potential of our proposed method, we conducted a comprehensive set of experiments utilizing simulated data. The results were not only able to demonstrate the enhancement of robustness of the SAR system in dealing with multipath but also highlighted the ability of our approach to deliver highly accurate and high-quality real-time imaging of the scene being surveyed.

Coherent compact Single-Input-Multiple-Output (SIMO) SAR formations have been studied as an attractive alternative to the standard monostatic SAR systems in terms of resolution and swath size. Significant gain in performance can be achieved given that the along-track (AT) spacing is well calibrated. We propose an innovative solution to the problem of AT position knowledge, using ambiguities of isolated point targets. A theoretical model of the interferometric ambiguity phase is provided, showing the direct relation to the AT baseline. Focusing the ambiguity allows us to increase its intensity, making the algorithm feasible even in the presence of clutter. The achievable accuracy is discussed theoretically and based on simulation.

This paper investigates the potential for accurate retrieval of Snow Water Equivalent (SWE) using an across-track formation of Synthetic Aperture Radar (SAR) satellites.

This paper compares two techniques for obtaining forest height and vertical structure from synthetic aperture radar (SAR) data, namely SAR tomography (TomoSAR) and phase histogram (PH). The comparison is carried out on an experimental basis by using the tomographic SAR dataset from the TomoSense campaign, flown by ESA in 2020/21 to support investigation of forested area for future low frequency spaceborne SAR missions. Both techniques were tested using data at full and degraded resolution. Experimental results show that the PH technique can only loosely approximate the forest vertical structure produced by SAR tomography, although it was able to achieve a fairly good estimate of forest height if the appropriate range of height of ambiguity is used. A degraded performance of the PH technique when applied to low-resolution data indicates that this technique is best fit for the case of high-resolution data, consistently with the assumption of the presence of dominant scatterers. Overall, these findings indicate the PH technique as an interesting option in the context of high-resolution spaceborne missions.

The new ESA TomoSense campaign aims at investigating a temperate forest located at the Eifel natural park, north-west Germany by means of Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Multifrequency (P, L, C), tomographic SAR data were acquired by repeated flights at different heights. Particularly in L- and C-band surveys, two aircrafts were simultaneously flying operated in a single-pass bistatic interferometric configuration. Such dataset could motivate advanced SAR technologies, and support scientific applications for future spaceborne SAR missions. However, a direct tomographic reconstruction on TomoSense L-band data presented unwanted artifacts due to: i) uncertainties in provided navigational data, and ii) a potential presence of clock mismatches as no dedicated communication link was employed for time synchronization. A dedicated calibration approach is therefore developed to compensate above disturbances using natural scatterers. Experimental results indicate that our proposed calibration approach is able to remarkably enhance the interferometric and tomographic performances on TomoSense L-band data.

This article discusses the effect of multipath in automotive radar imaging under different sensor configurations. The study is motivated by the fact that radar technologies are becoming indispensable in the automotive scenario. Many applications such as collision avoidance systems, assisted parking, and driving assistance systems take advantage of radar technologies to accomplish their task. However, one of the main concerns about automotive radars is the possibility of detecting false targets due to multiple signal reflections. In this article, we show how different sensor layouts experience multipath differently. In particular, we demonstrate that with multiple-input multiple-output (MIMO) radars, what really matters is the physical positions of the transmitting and receiving antennas. The monostatic/bistatic equivalent configurations cannot be used to design a system and to simulate an acquisition in the presence of a multipath. We also demonstrate how vehicle-based MIMO-synthetic aperture radar (MIMO-SAR) imaging can generate a bi-dimensional aperture which significantly reduces multipath effects in the focused image, avoiding the detection of false targets. All the theoretical analyses are supported by several simulations where different sensor layouts are tested, and the capability of MIMO-SAR to reject multipath is validated.

With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding environment. Synthetic Aperture Radar (SAR) systems increase the resolution of conventional mass-market radars by exploiting the vehicle’s ego-motion, requiring very accurate knowledge of the trajectory, usually not compatible with automotive-grade navigation systems. In this setting, radar data are typically used to refine the navigation-based trajectory estimation with so-calledautofocusalgorithms. Although widely used in remote sensing applications, where the timeliness of the imaging is not an issue, autofocus in automotive scenarios calls for simple yet effective processing options to enable real-time environment imaging. This paper aims at providing a comprehensive theoretical and experimental analysis of the autofocusrequirementsin typical automotive scenarios. We analytically derive the effects of navigation-induced trajectory estimation errors on SAR imaging, in terms of defocusing and wrong targets’ localization. Then, we propose a motion estimation and compensation workflow tailored to automotive applications, leveraging a set of stationary Ground Control Points (GCPs) in the low-resolution radar images (before SAR focusing). We theoretically discuss the impact of the GCPs position and focusing height on SAR imaging, highlighting common pitfalls and possible countermeasures. Finally, we show the effectiveness of the proposed technique employing experimental data gathered during open road campaign by a 77 GHz multiple-input multiple-output radar mounted in a forward-looking configuration.

3-D imaging using SAR tomography is a well-recognized technique for the characterization of forested areas. Studies revealed that the intensity of radar echoes originating from specific locations within the canopy of forest could be used to estimate its above ground biomass. Moreover, a recent work proposed an estimation technique using a pair of interferometric SAR images only. The images are combined in order to cancel contributions from the ground, and to roughly estimate the volume reflectivity. This paper proposes to study the influence of temporal decorrelation of this minimalist approach, which relies on the hypothesis of perfectly correlated signals. A model, based on second order statistics, is proposed and is used to predict the influence of temporal decorrelation of the relative error of the above ground biomass estimation over tropical forests measured at$\mathrm{P}$band.

The new ESA TomoSense campaign includes both airborne and in-situ measurements over a temperate forest in northern Germany. SAR surveys are complemented by several LiDAR acquisition thus making one of the most complete datasets available for forest studies. Tomographic, fully-polarimetric and opposite views acquisitions are available at P- L- and C-bands; furthermore, both monostatic and bistatic data are available at L- and C-bands. These latter acquisition modes required ad-hoc calibration strategies for clean tomograms to be obtained. Also, the baseline distribution of the L-band data motivated the creation of a new model-based tomographic approach for mono-bistatic pairs. The effectiveness of the proposed processing chain is here proved with coherence maps and tomographic profiles. The quality of the tomographic reconstruction is also confirmed by comparing estimates of biophysical parameters with LiDAR measurements.

The BIOMASS DEM Product Prototype Processor (BIO-DEMPP) is being developed in the frame of ESA's Earth Explorer BIOMASS mission. The prototype includes a complete interferometric SAR chain, from the stack co-registration until the mosaicking of the derived height products (Digital Elevation and Digital Terrain Models). This paper presents an overview of the BIODEMPP architectural design and its validation strategy, as well as first results obtained with simulated BIOMASS-like data.

Automated driving requires a huge number of on-board sensors to provide advanced functionalities, from parking assistance to emergency braking and environment mapping for target recognition/classification. While low-cost automotive-legacy radars are mostly used for target detection due to their limited angular resolution, vehicular Synthetic Aperture Radar (SAR) is emerging as a promising imaging solution, provided that the motion is known with high accuracy. This paper assesses the benefits of a navigation-augmented SAR system exploiting multiple on-board sensors, e.g., Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), odometers and steering angle sensors. The results confirm the potential of the proposed multi-sensor-aided SAR system to obtain centimeter-level accurate images of the driving scenario.

This paper introduces a multi-static Synthetic Aperture Radar (SAR) mission concept for high resolution 3D imaging at frequencies below 1 GHz, for which the available bandwidth allocated to Earth Observation is limited. Resolution improvement is achieved by the Fundamental Relation of Diffraction Tomography (FRDT), leading to a satellite formation where multiple transmitters are flown on the same orbit with a separation of hundreds of Km, while receivers are deployed on slightly different orbits to form interferometric baselines. For each receiver, such a formation allows for the generation of 2D SAR images with an equivalent bandwidth increase proportional to the number of transmitters, whereas 3D imaging is obtained by combining SAR images from all receivers. Beside hardware requirements - not considered in this paper - the fundamental challenge posed by this configuration is management of multiple transmissions. We show that signals from different receivers can be separated at the receiver based on the associated Doppler and direction of arrival, enabling simultaneous transmission and reception. The concept is supported by results from numerical simulations of multistatic SAR data.

Scheduled for launch in 2023, ESA's seventh Earth Explorer Mission, BIOMASS, will carry the first P-band synthetic aperture radar (SAR) to be flown in space, to gather fully polarimetric acquisitions over forested areas worldwide in interferometric and tomographic modes. This paper presents the algorithms developed to estimate biophysical parameters from BIOMASS measurements and their implementation in the BIOMASS level 2 (L2) prototype processor. The L2 processor will generate global maps of forest Above Ground Biomass (AGB), Forest Height (FH), Forest disturbance (FD). Accurate generation of these products requires the L2 processor to be closely inter-linked with the BIOMASS interferometric processor, in order to produce phase-calibrated interferometric stacks, retrieve sub-canopy terrain topography, and generate a 3D representation of forest structure by use of SAR tomography. AGB estimation results are here shown using BIOMASS-like acquisitions derived from campaign data acquired over six tropical forests in South America and Equatorial Africa.

Polarimetric Synthetic Aperture Radar Tomography (TomoSAR) is a technology to image the three-dimensional (3D) structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. Several experimental studies by different research groups demonstrate that the use of the 3D information results in an accurate characterization of forested areas, providing access to a number of biophysical variables such as terrain topography below the vegetation, forest height, forest Above Ground Biomass (AGB), and forest classification. This paper is intended to provide the reader with an introduction to the use of TomoSAR for the characterization of forest areas, addressing basic imaging principles and methods, retrieval of biophysical parameters, and perspective for spaceborne missions.

The TomoSense experiment comprises campaign and research activities in support of future Synthetic Aperture Radar (SAR) mission concepts at P-, L-, and C-band by the European Space Agency (ESA). The research is intended to provide a quantitative basis for the evaluation of single-pass interferometry over temperate forests at L- and C-band and investigate potential synergies between C-band convoy mission concepts and future P- and L-band missions. SAR acquisitions include P- L-, and C-band data acquired at the Eifel National Park in Germany by flying approximately 25 trajectories to provide tomographic imaging capabilities. Land C-band data were acquired by simultaneously flying two aircraft to gather bistatic data with varying interferometric baselines. Field activities include forest census (dbh, tree height and species) at 80 plots and Terrestrial Laser Scanning (TLS). The dataset is complemented by small-footprint Airborne Lidar Scanning (ALS) and derived products. Preliminary results are here shown relative to polarimetric tomography at P-band and L-band imaging.

This paper describes the rationale and development of the estimation techniques for the level-2 data products of the European Space Agency's 7th Earth Explorer BIOMASS mission. BIOMASS is planned for launch in 2023 and will carry the first-ever P-band synthetic aperture radar (SAR) onboard a satellite. It has been designed to produce consistent global maps of the Earth's forests during a nominal five-year lifetime. Fully polarimetric SAR data will be collected and the satellite orbit will be selected for repeat-pass interferometry and tomography in separated mission phases. Mission requirements call for three level-2 data products: above-ground biomass, forest height and forest disturbance. The paper also discusses the expected limitations of the estimation techniques and remaining problems to be addressed.

The new ESA TomoSense campaign aims to explore the retrieval of biophysical quantities over forests for different acquisition geometries and radar parameters. Tomographic SAR acquisitions are currently being carried out using different wavelengths, both monostatic and bistatic systems and opposite views. This work presents the current advances in the analyses and calibration of the TomoSense data stacks to make them suited for scientific analyses. Airborne monostatic P-band acquisitions as received by MetaSensing presented artifacts connected to the acquisition geometry. Coherence and phase fluctuations were compensated thus obtaining clean tomographic reconstructions and a clear identification of the terrain level. Bistatic L-band data are expected to be available in short time as well.

P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity.

Tomography SAR (TomoSAR) methods recover the 3D structure of targets by processing several SAR images simultaneously. Depending on the degree of approximation, recovering the vertical structure can amount to a 1D problem (processing a vector of pixels), a 2D problem (processing a matrix) or a 3D problem (processing the whole 3D stack at once). The computational burden decreases from the 3D to the 1D, but the constraints for a proper reconstruction are tighter. Hence, this paper discusses the limit and criterion for the feasibility of each method. The huge computational burden of TomoSAR 3D method is addressed by a fast implementation on GPUs. Theoretical analyses and our approach are demonstrated on simulated data, as well as on real data from the ESA AlpTo-moSAR campaign.

SAR tomography is a powerful tool for analyzing forested environments. ESA seventh Earth Explorer BIOMASS will be the first spaceborne tomographic mission at P-band returning three dimensional reconstruction of the tropical vegetation. The backscattered intensity coming from specific depths inside the forest layer can be effectively related to biophysical parameters as tree height or biomass amount. Biomass estimates are very sensitive to power fluctuations in the measurements that, therefore, have to be minimized. In this work, the tomographic power fluctuations induced by irregular acquisitions and missing images are addressed. Compensation strategies are presented and their effectiveness is demonstrated using real data gathered on tropical forests.

In this letter, we present an experimental assessment of vegetation height retrieval in tropical forests based on P-band synthetic aperture radar (SAR) acquisitions. Two approaches are implemented and compared: 1) parametric height estimation by minimizing the least-square problem between random volume over ground (RVoG) model predictions and multibaseline SAR data and 2) thresholding the vertical backscattering profiles that are focused by SAR Beam-forming tomography. The data set under analysis is from the ESA AfriSAR campaign that was flown over Gabon in 2016. Results show that at a resolution of 25 m × 25 m, which corresponds to about 80 independent looks, both of the two approaches are able to retrieve forest height to within an accuracy of about 3 m or better over the interval of forest height between 30 and 50 m when compared to Light Detection and Ranging (LiDAR) measurements.

A method is presented to estimate and compensate the ionospheric and clock-drift perturbations that affect bistatic synthetic aperture radar (SAR) images acquired under a quasi-monostatic acquisition geometry. This is accomplished through multisquint-based processing of the interferometric phase, which allows separating the ionospheric component from the rest of the phase perturbations by processing small azimuth subapertures. It is demonstrated how the absolute, i.e., nondifferential, ionospheric phase can be estimated by exploiting the baseline of the acquisition geometry, which further allows an individual correction of each image of the bistatic pair. A mathematical model of the bistatic SAR phase perturbations, as well as an algorithm for performing their estimation and compensation, is presented. The performance of the method is assessed with end-to-end simulations of bistatic acquisitions over synthetic distributed targets.

A new processing technique, i.e., ground cancellation, which removes the ground signal from a pair of interferometric synthetic aperture radar (SAR) images, is used to emphasize the response from above-ground targets. This technique is of particular interest when studying forest canopies using low-frequency signals able to reach the underlying ground, in which case the portion of the signal coming from the ground interferes with the recovery of information about the vegetation. We demonstrate that the power in ground-canceled P-band HV SAR data gives significantly higher correlations with above-ground biomass (AGB) than the interferometric images considered separately. In addition, a significant increase in the sensitivity of backscatter to AGB is observed. Ground-canceled power may then be modeled or regressed to estimate AGB; these possibilities are not discussed here as they will be the topic of forthcoming publications. The effectiveness of this technique is proven through simulations and analysis of real data gathered on tropical forests. The stability of the technique is analyzed under the digital terrain model and baseline control errors, and compensation strategies for these errors are presented.

The ESA BIOMASS mission will be the 7th Earth Explorer measuring the above-ground biomass (AGB) in the world's forests. The current ESA Level-2 (L2) implementation study focuses on defining and implementing the main algorithms for forest parameter retrieval from BIOMASS data. After the first year of L2 study innovative results were achieved: the development of ground cancellation, in particular, has proved to be huge value, since it removes from the data the effects of environmental variability and contributions unrelated to the forest carried in the ground scattering. In this paper the current processor implementation and validation activities of the L2 team will be described.

In this work we investigate the role of volume scattering obtained from tomography and ground/volume decomposition in retrieving AGB (Above Ground Biomass). Results here presented originate from the BIOMASS L2 study, aimed at defining and implementing the tomographic and interferometric processors of the BIOMASS mission. In particular we aim at discussing whether, and to what extent, ground/volume decomposition can provide a valid alternative to tomography. To do this, both are tested based on the P-Band data collected at the forest site of Paracou, French Guiana, during the TropiSAR campaign, and validated against in-situ AGB measurements in terms of correlation and sensitivity of the retrievals. Quite surprisingly, results indicate that volumebackscattered power as obtained by ground/volume decomposition is almost unsensitive to AGB, notwithstanding different solutions for volume scattering are tested, and lead to conclusion that forest structure actually plays a non-negligible role in AGB retrieval in tropical areas.

Stock volume is an important forest inventory parameter. In case of agro-forests and plantation forests, stock volume estimates are important as they provide reliable indicator of the productivity of these species. In this study stock volume loss due to harvest of polar plantations between 2017 and 2018 are estimated using ALOS-2/PALSAR-2 backscatter data. Using simple linear regression models the AGB of the plantations before and after harvest are estimated. These are converted to stock volume loss per hectare. From field inventory, the actual stock volume during harvest are measured. These are validated against the estimations using two models - M1 and M2. Model M1, utilizes only HV-pol backscatter data and provides a lower accuracy with r2= 0.46. Model M2 utilizes HH- and HV-pol backscatter and provides stock volume loss estimation with r2= 0.51.

The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

The structure of forests, in terms of mass and the three-dimensional arrangement of individual trees, is a direct indicator of how much carbon is stored in the ecosystem, which in turn, has a profound effect on how the ecosystem functions and cycles carbon, water, and nutrients (Shugart et al., 2015). There is an increased need to understand local to global storage and dynamics of carbon in terrestrial vegetation, as carbon storage is a prerequisite to understanding the coupling of the biosphere to other components of Earth systems including the climate. The BIOMASS mission of the European Space Agency (ESA), to be launched in 2021-2022 will provide, for the first time, synthetic aperture radar measurements at P-band frequency (~70 cm wavelength) and tomographical (TomoSAR) imaging capability to quantify forest structure and above ground biomass.

The problem of estimating above ground biomass in tropical regions has been recently tackled by using tomographic SAR data at low frequencies. The added value of tomography is the possibility of focusing on specific heights inside of the vegetation layer, rejecting the echoes coming from other elevations at the same time; in particular, the strong echoes coming from the ground level are greatly attenuated. Recently, a simpler algorithm aiming at this goal has been proposed: the interferometric ground notching. According to this algorithm, two InSAR images are coherently combined to cancel out the ground echo and emphasize the forest backscattering. However, any time lag between the two images introduces temporal decorrelation which, in turn, affects the effectiveness of the coherent subtraction. This work shows an analysis of the effect of the temporal decorrelation from a theoretical point of view and through experiments on real data; results from a boreal forest and a tropical one are presented. As predicted by the theory the impact on the radiometric stability results limited to within 0.5-1dB for taller forest where most of the biomass is stored.

Due to the considerable resources investment, fine tuning the parameters of a spaceborne SAR system far in advance is very important. Most of them can be set by resorting to synthetic data, however models of complex natural phenomena are often not reliable enough to drive the choice. In this case, real data coming from airborne campaigns might be used as long as it is properly translated in a spaceborne setting. The problem of simulating spaceborne acquisitions was recently tackled and led to the definition of a new algorithm here exploited to analyze the effect of small changes in the system parameters. This work presents an analysis of the bond between biomass and tomography varying the orbits of the simulated spaceborne system. Different look angles and total baseline apertures are explored; moreover, random fluctuations of the trajectories are considered. These analyses provide recommendations about the nominal orbits and their accuracy.

This paper focuses on the retrieval of terrain topography below dense tropical forests by means of synthetic aperture radar (SAR) systems. Low-frequency signals are needed to penetrate such a thick vegetation layer; however, this expedient alone does not guarantee proper retrieval. It is, here, demonstrated that the phase center of P-band backscatter may lie several meters above the ground, depending on the slope and incidence angle. SAR tomography is shown to overcome this problem and retrieves the actual topography even in the presence of dense trees up to 50 m tall. Digital terrain models returned by SAR tomography are, here, put in comparison with light detection and ranging (LiDAR) terrain models: the accuracy of radar-derived maps is found to be at least comparable with the one offered by LiDAR systems. Moreover, the discrepancy between tomography and LiDAR is larger if large-footprint LiDAR is considered thus suggesting that, in this case, tomographic maps should be considered the reference height. Analyses are carried out by processing three data sets gathered over different tropical forests in western Africa. The robustness of the radar estimates is assessed with respect to both ground slope and treetop height.

In this paper, the impact of changing weather conditions on repeat pass SAR tomography is addressed to support the upcoming spaceborne mission BIOMASS. In recent years it has been demonstrated that forest biomass retrieval can be improved by using P-band SAR tomography in tropical forest. Yet, these results were obtained by using campaign data acquired in a single day, while the revisit time of BIOMASS mission will be 3-4 days. To fill this gap, we simulate BIO-MASS repeat pass tomography using ground-based TropiS-CAT data with revisit time of 3 days and rainy days included. It is observed that the backscattered power within canopy layer, which is significantly correlated to the forest biomass, stays stable under changing weather conditions. The backscattered power variation of canopy layer are within 1.5 dB. For this forest site, this error is translated into an AGB error of about 50-80 t/ha, which is 20% or less of forest AGB.

The effectiveness of SAR tomography in estimating forest Above Ground Biomass (AGB) has been repeatedly demonstrated in the recent years. For tropical rain-forests, analysis from the Paracou test site reveals that the best results are achieved when the backscattered power coming from 30m above the ground is considered. As suggested in previous papers, the most likely reason is that ground scattering acts as a disturbing factor for forest biomass retrieval, as it depends on a number of parameters (like topography, moisture), that do not relate to forest biomass. In this paper we further test this hypothesis by proposing the concept of interferometric ground notching. By taking the difference between two phase calibrated, ground-steered, SAR SLC images a third image is obtained where ground scattering contributions are canceled out, hence the name ground-notched SLC. Results indicate that ground-notched data can effectively retain the features of vegetation-only scattering, including its polarimetric signature and correlation with AGB.

This paper concerns processing techniques for the the characterization of a tropical forest using PolTomSAR data at P band. In particular, existing forest biomass estimation methods, relating biomass to sampled tomographic intensity values, are revisited using simple methodological step-sand an adaptive tomographic intensity sampling approach. The canopy reflectivity sampling location is determined as a function of the effective forest height and of the tomographic resolution, in order to compensate geometrical mismatches. Moreover, an adaptive polarimetric decomposition technique is used to further decouple the sampled intensity from ground and topographic tomographic scattering effects. The performance of the proposed techniques is assessed using TROPISAR P-band data acquired by the ONERA's SETHI sensor over the Paracou data site in French Guiana in 2009. Results indicate over this site a substantial reduction of the Above Ground Biomass (AGB) estimation error, with respect to existing techniques.

The objective of this paper is to provide a better understanding of tomographic capabilities to estimate above ground biomass (AGB) in dense forested areas at P-band. The analysis is carried out on airborne data acquired over sites in French Guyana and in Gabon during the ESA campaigns TropiSAR and AfriSAR 2015, respectively. Over both sites, P-band tomography allows us to retrieve the vertical structure of the forest, to better characterize the ground and/or volume scattering mechanisms and to provide a unique solution for the AGB retrieval over the full range of biomass. The relationship between AGB and tomography data was found to be highly similar for forests across continents and sites: Paracou (French Guiana), Lope, Rabi and Mondah (Gabon). The developed metrics derived from the tomographic data have been found highly correlated to reference in situ AGB estimates (R2=0.85) and the root mean square error was 16% (for AGB ranging from 0 to 500 t/ha). These results have strong implications for the tomographic phase of the BIOMASS spaceborne mission.

The BIOMASS mission gives completely new challenges in external calibration arising from the orbital pattern needed for the tomographic and Pol-InSAR phases of the mission, the strong effects of the ionosphere at P-band, and the lack of pre-existing P-band data except over very limited parts of the globe. Together these create problems that can only be solved by combining infrequent visits to instrumented calibration sites with systematic exploitation of the properties of distributed targets and targets of opportunity. Proposed approaches to performing radiometric and polarimetric calibration are described, together with meeting geolocation accuracy requirements.

This paper presents a new algorithm for forest biomass estimation from P-band synthetic-aperture radar (SAR) backscatter data, notch-filtered at ground-level. A semi-empirical model is fitted to spatial and polarization trends in the backscatter data and no reference biomass data are needed for training. An evaluation on airborne P-band SAR data from a tropical test site in Gabon results in a root-mean-square error lower than 20% and a correlation better than 90%.

The Earth Explorer Biomass mission will provide the scientific community with accurate maps of tropical, temperate and boreal forest biomass, including height and disturbance patterns. This information is urgently needed to improve our understanding of the global carbon cycle and to reduce uncertainties in the calculation of carbon stocks and fluxes associated to the terrestrial biosphere. It is also crucial for approaches to managing climate, such as the UNFCCC initiative known as Reducing Emissions through Degradation and Deforestation (REDD+), aimed at climate change mitigation through conservation and better management of tropical forests The required measurements are forest biomass and forest height at resolution of 200 m, and detection of deforestation at 50 m. Global maps of biomass are required with accuracy of 20% (or l0 t ha-1when above-ground biomass are less than 50 t ha-1). To achieve this Biomass will be implemented as a P-band SAR mission. It will exploit the unique sensitivity of P-band SAR together with advanced retrieval methods including polarimetric interferometry (Pol-InSAR) and SAR tomography to measure biomass, height and disturbances across the entire biomass range every 6 months. The mission will also support important secondary objectives, including sub-surface imaging in arid zones, production of a bare-earth DTM and ice applications.

Forest biomass is a most important parameter in the context of the global carbon cycle. Mapping above ground biomass (AGB) at a global scale contributes to understanding the dynamics of climate change. Tropical forests are extremely important as they store more biomass. In recent years, SAR tomography has been introduced as a new technique that has shown enormous potential in AGB retrieval. A strong linear relationship between in-situ measurements and tomographic power from 30 m above the terrain was discovered by previous studies carried out in French Guiana. However, the two parameters that determine the linear relationship might vary for different tropical forests. Due to the great difficulty in measuring tropical forest AGB by field surveys, in-situ measurements is unfeasible to relate SAR tomography for mapping global forests AGB. For purpose of solving this problem, we investigate the possibility to use LiDAR derived AGB to find the two parameters of the fit line. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept.

This paper presents the results achieved by SAR tomography in estimating digital terrain models under tropical forests. Several airborne data stacks have been processed, they have been gathered on dense forests in central Africa in the framework of the AfriSAR campaign and in South America. The joint exploitation of polarimetry and multi baseline interferometry enabled to separate ground from vegetation above and to analyze it alone. Also, airborne LIDAR measurements were available and provided a reliable comparison. Results indicate that terrain topography in tropical forests can be retrieved by P-Band SAR Tomography to within an accuracy at least comparable to that of LIDAR systems. Furthermore, few meaningful details visible in SAR derived DTMs are missing in LIDAR maps probably due to the high density of the vegetation layer.

This paper describes a geometrically rigorous approach for generating a synthetic SAR Tomographic data-set starting from a real one acquired from a different geometry, using large pulse bandwidth and eventually a (slightly) different carrier frequency. This change is made possible by properly taking into account the spectral properties of the scene under observation. Special attention has been paid to the possibility of simulating spaceborne data starting from airborne ones. Data of the forthcoming ESA BIOMASS mission have been simulated from airborne campaigns on tropical forests. The simulated tomographic data preserves the original vertical structure of the illuminated scene as well as total backscat-tered power, while ensuring full consistency between the resulting 3D Impulse Response Function (IRF) and the simulated geometry. The simulation is demonstrated to preserve the same correlation to forest Above Ground Biomass (AGB) as the original airborne data-set and a high sensitivity too.

A tomographic synthetic aperture radar (TomoSAR) represents a possible route to improved retrievals of forest parameters. Simulated orbital L-band TomoSAR data corresponding to the proposed Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS) mission (1.275 GHz) are evaluated for retrieval of above-ground biomass in boreal forest. L-band data and biomass measurements, collected at the Krycklan test site in northern Sweden as part of the BioSAR 2008 campaign, are used to compare biomass retrievals from SAOCOM-CS to those based on SAOCOM SAR data. Both data sets are in turn compared with the corresponding airborne case, as represented by experimental airborne SAR through processing of the original SAR data. TomoSAR retrievals use a model involving a logarithmic transform of the volumetric backscatter intensity, Ivol, defined as the total backscatter originating between 10 and 30 m above ground. SAR retrievals are obtained with slope-compensated intensity γ0using the same model. It is concluded that tomography using SAOCOM-CS represents an improvement over an airborne SAR imagery, resulting in biomass retrievals from a single polarization (HH) having a 26%-30% root-mean-square error with a little to no impact from the look direction or the local topography.

We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space-time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.

This work presents a model of phase perturbations affecting bistatic SAR L-band acquisitions, along with a multisquint-based compensation method. It is shown how this method is able to discriminate each component of the phase screens, thus allowing a more accurate correction scheme. The phase compensation accuracy is assessed on the recovery of each individual screen and on tomography by generating time-domain simulations of bistatic SAR images. Perturbations are introduced starting from the RAW data, subsequently recovering each screen from the multisquint processed sub-bands and performing the corrections. The recently proposed SAOCOM-CS tomographic configuration (quasi-monostatic geometry) is taken as reference for the simulations.

This paper proposes different processing techniques for the polarimetric 3-D imaging of forested areas using multi-baseline interferometric SAR data, acquired in tandem configuration from spaceborne SAR sensors. Tandem-like acquisition modes, based on the simultaneous measurement of interferometric pairs, represent a high-potential alternative for the tomographic imaging of scenes with rapidly decorrelating scattering features using a spaceborne SAR. The counterpart related to this independent interferometric sampling lies in the restricted amount of available information, whose processing requires specific techniques. These methods as well as their potential for boreal forest characterization are evaluated in the frame of the preparation of the SAOCOM CS mission using ESA's BIOSAR II campaigna data sets acquired at L band by the DLR ESAR sensor.

3-D SAR tomography is an active radio remote sensing technique, stemming from synthetic aperture radar (SAR) interferometry, allowing the advanced functionality of fully three-dimensional imaging. Typical application is to scenarios with multiple height-distributed point-like scatterers, or with volumetric scatterers, allowing the solution of layover in urban or infrastructure areas, and the reconstruction of the vertical structure of forest or ice layers. This new 3-D radar imaging and information extraction ability is very important in complex remote sensing areas such as biosphere and cryosphere monitoring, related to critical environmental problems of global warming and climate change. After first theoretical and experimental investigations started around the 2000, thanks to many developments from several SAR remote sensing groups SAR tomography is now also being applied experimentally to new dedicated spaceborne SAR missions. The 3-D tomographic concept has been also extended to higher output dimension in the more recent differential tomography methods, producing 4-D (3-D + time) images, so bridging the gap between the mature differential interferometry and the advanced SAR tomography. Typical application in this case is to urban or complex infrastructure scenarios for improved deformation monitoring, in terms of density of the measurements, accuracy, and coverage of specific zones for single building application where layover phenomena can impair full deployment of differential interferometry. Application of 4-D differential tomography to forest layers with temporal decorrelation has also been proposed. This paper present an overview of the main state-of-the-art processing methods and typical experimental applications for three-dimensional and higher-dimensional tomographic SAR imaging, developed during the last decade or more, as an extension and updating of previous review papers. New trends for future developments are also pointed out.

The objective of this paper is to provide a better understanding of tomographic capabilities in characterization of dense forested areas at P-band. The analysis is carried out on airborne data acquired by ONERA over the site in French Guyana, and in Gabon during the ESA campaign TropiSAR 2009 and AfriSAR 2015, respectively. The results shown support the idea that ground- and -volume interactions play a significant role at P-band. For a dense forest of 30 m and more, strong ground contribution at P-band can be visible in tomograms. P-band tomography allow us to retrieve the whole forest vertical structure, better characterizing of the ground and/or volume scatterings and providing an unique solution in high biomass ranging from 0–500 t/ha.

In this work we discuss the differences between SAR tomographic analyses produced by direct 3D focusing, which we refer to as coherent tomography, and by processing simultaneous interferometric pairs collected in different passes, which we refer to as incoherent tomography. While the application of coherent tomography using space-borne sensors is often hindered by temporal decorrelation, incoherent SAR tomography appears to be a viable solution upon the condition that simultaneous InSAR pairs are available, which is possible by using bistatic SAR systems. For this reason, this paper is focused on assessing the capabilities of incoherent tomography, and on discussing the implications for bistatic SAR systems. Examples are shown based on simulated SAOCOM-CS data.

The Diffraction Tomography Theorem states that the full response of a weak scattering body to illuminating monochromatic plane waves coming from all directions is the Fourier spectrum of the reflectivity. This well known fact has been exploited in seismic and acoustic analyses but not as much for radar, as bistatic receivers have rarely been used. This paper intends to recall the DTT, and illustrate the immediate implications in the case of constellations of low frequency spaceborne Synthetic Aperture Radars (SAR), whose performance are severely limited by bandwidth restrictions imposed by ITU regulations. We will show that each passive receiver provides a specific region in the wavenumber domain. Those regions can be combined to form a bigger one by properly positioning the receivers, therefore increasing spatial resolution. This process is conceptually analogous to forming a tessellation using a number of small tiles, hence the title of this paper. Using this concept, we will show that the use of N additional passive receivers allows an N-fold increase of the slant range resolution. For example, the use of just two additional receivers would increase the slant range resolution achievable at P-band from 25 m to about 8 m, still respecting the 6 M H z limit.

In this work, we discuss the retrieval of information about the vertical structure of the ionospheric phase by means of Multi-Squint Interferometry (MSInSAR). A model of the MS phase is proposed that accounts for multiple ionospheric layers and residual topographical terms. This model is then generalized to the case of a continuous distribution, which can be retrieved from the MS phase via a 2D Fourier Transform. Moreover, we demonstrate the possibility to single out the phase screen at each layer, plus the residual topographic phase. The inversion procedure is demonstrated through numerical simulations, based on BIOMASS system parameters.

The availability of accurate trajectory information is paramount for the processing and exploitation of synthetic aperture radar (SAR) data. Considering the particular case of spaceborne SARs designed for repeat-pass interferometric applications, errors in the trajectory translate into phase artifacts that affect the interferometric performance. In this paper, we propose a model-based procedure to calibrate the trajectories of spaceborne SAR systems by the multisquint (MS) phase. The technique allows to estimate the along and the derivative of across track geometric errors. The geometric model of the InSAR phase is derived as a function of positioning errors and the MS phase model as derivative of the InSAR phase geometric model, with respect to the squint angle. We perform a sensitivity analysis of the model in order to define which geometric errors can be estimated by the MS phase, justifying the assumption that the MS phase is very poorly affected by the atmospheric phase screen. We particularly concentrate on the TOPSAR acquisition mode, where the phase is very sensitive to geometric errors. We start from the classical two-image case and then consider the extension to the multibaseline case. Experimental results obtained by processing of interferometric pairs acquired by the Sentinel-1A sensor are reported.

This paper presents new experimental results of 3-D imaging using tomographic techniques over a snow covered sea ice medium, sensed with an X-band radar system. The available data are from a ground-based synthetic aperture radar data collection campaign carried out over Kattfjord, Tromsø, Norway. Direct imaging of the vertical structures of the radar reflectivity of the snow and sea ice layers is achieved by focusing the signal from a 2-D synthetic array in the 3-D space. The effect of a change in propagation velocity of the wave inside the considered medium is investigated in the focusing process, and the tomograms are effectively corrected for this effect. The distribution of the scattering contributions in the vertical direction reveals a strong response from the sea ice cover. Tomograms at two different polarizations are investigated and compared. The results and the interpretations are also supported by the simulated data from the same system.

This paper presents new principles and techniques to perform High Resolution (HR) 3-D imaging of volumetric environments using Polarimetric SAR Tomography (POLTOMSAR) and Multi-Baseline Polarimetric and Interferometric SAR (MB-POL-inSAR) data. Unlike classical polarimetric spectral estimation approaches which consider polarization as way to improve the discrimination between vertically aligned scatterers, or to estimate unitary rank polarimetric scattering features [1] [2], this paper provides full rank techniques which permit to estimate 3-D coherency matrices that can be characterized using classical polarimetric processing algorithms. The algorithms investigated here, Beamformer, Capon and MUSIC, have a relatively low numerical complexity and varying levels of resolution. A novel approach is developed to estimate 3-D full rank polarimetric covariance matrices with HR spatial properties.

This work aims to describe the characteristics and the status of development, including the results of a first preliminary testing campaign, of a low frequency airborne imaging radar developed in Italy for the Italian Space Agency.

Every day, ships of different type, size and origin cross the world seas. Not only for commerce and transport, but also for illegal activities. In addition to conventional positioning and tracking systems, detection with Earth observation satellites is an effective means to monitor human movements across the sea. The European Copernicus Programme operates towards this goal, through the definition of border and maritime surveillance as one of its main tasks. This paper describes an Object Based Image Analysis (OBIA) workflow developed for ship detection, monitoring and tracking with high-resolution satellite images. Here, it has been used to simulated medium-resolution multispectral (MS) and Synthetic Aperture Radar (SAR) images representative of the Sentinel components of Copernicus. First results confirm that the method proposed can be efficiently used by European agencies for monitoring the explosive growth of illegal flows in the Mediterranean Sea.

Synthetic Aperture Radar (SAR) Tomography (TomoSAR) provides access to the three-dimensional (3D) structure of illuminated media by jointly focusing multiple SAR acquisitions. TomoSAR imaging can be understood in simple terms by considering that multiple SAR flight lines, or orbits, allow forming a bi-dimensional synthetic aperture, resulting in the possibility to resolve the targets not only in the range-azimuth plane, but also in elevation. This simple principle brings along unprecedented possibilities, providing a way to investigate the illuminated media based on a direct observation of their vertical structure. The aim of this paper is to provide the readers with a brief tutorial on the use of TomoSAR imaging in the remote sensing of distributed media, by presenting basic imaging principles, applications, signal processing methods, and identifying challenges for future tomographic SAR systems.

A fundamental requirement for coherent processing of repeat pass SAR data stacks is to have precise knowledge of the relative position of each track. Indeed, sub-wavelength position errors give rise to residual phase screens among different passes, which hinder coherent applications. In this paper we describe an approach to estimate and remove phase screens by exploiting distributed targets, based on the concept of equivalent phase center. The proposed approach is demonstrated through numerical simulations and using campaign data. A cross-check of the results from simultaneous P- and L-Band acquisitions indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters. Preliminary results indicate that Capon-based tomographic imaging is more sensitive to phase errors, potentially resulting in artifacts that do not appear in Fourier-based approaches.

In this letter, we propose a new methodology to estimate the absolute digital elevation model (DEM) of an area by radargammetric-like processing of interferometric multibaseline synthetic aperture radar (SAR) data from two opposite-side surveys. Two DEMs of the imaged area obtained from two opposite-side tomographic SAR views are coregistered, correcting residual baseline errors. This methodology combines the great accuracy of multibaseline interferometric processing with precise stereo plotting typical of opposite-side radargrammetry, requires no texture matching and no control points, and is applicable also in the case of few a priori information about the site topography.

In this paper, first results concerning the characterization of the subsurface of ice sheets and glaciers through single and multipolarization synthetic aperture radar (SAR) tomography (TomoSAR) are illustrated. To this aim, the processing of data acquired in the framework of the European Space Agency IceSAR 2012 campaign is discussed. IceSAR 2012 was conceived so as to support the secondary objectives of the future Earth Explorer mission BIOMASS, which will be a SAR instrument with media penetration capabilities due to the use of the P-band frequency. In this regard, a tomographic study of ice was motivated by the fact that cryospheric remote sensing is of fundamental importance in order to understand more in depth the morphology and the dynamic processes regulating ice sheets. The main objective of the tomographic experiment of the campaign herein discussed was indeed to assess the capability of P-band SAR to retrieve any information about ice subsurface structure. Imaging has been achieved through TomoSAR techniques, applied to airborne multibaseline data acquired in the southwest of Greenland. Different imaging approaches are compared, and the main results achieved are presented: It is found that scattering in the upper layers of glacial subsurface can be achieved up to an extent of about 20-60 m, conditional on the different types of glaciological zone observed. Moreover, clear morphological structures have been found beneath the ice surface at one of the investigated sites.

In this paper, we report results from the analysis of 3-D L-band airborne synthetic aperture radar (SAR) acquisitions acquired in March 2014 over the Mittelbergferner glacier, Austrian Alps, during the European Space Agency (ESA) campaign AlpTomoSAR. The campaign included coincident in situ measurements of snow and ice properties and ground-penetrating radar (GPR) data acquired at 600 and 200 MHz over a total length of 18 km. Radar data were acquired by repeatedly flying an L-band SAR along an oval racetrack at an altitude of about 1300 m over the glacier, such that two data stacks from opposite views are obtained. Data from all passes were coherently combined to achieve 3-D resolution capabilities, resulting in the generation of 3-D tomographic SAR (TomoSAR) cubes, where each voxel represents L-band radar reflectivity from a particular location in the 3-D space at a spatial resolution on the order of meters. TomoSAR cubes were finally corrected to account for wave propagation velocity into the ice, which was a necessary step to associate the observed features with their geometrical location, hence enabling a direct comparison to GPR data. The TomoSAR cubes show the complexity of the glacier subsurface scattering. Most areas are characterized by surface scattering in proximity of the ice surface, plus a complex pattern of in-depth volumetric scattering beneath and scattering at the ice/bedrock interface. Various subsurface features observed in GPR transects at 200 MHz clearly showed up in TomoSAR sections as well, particularly firn bodies, crevasses, layer transitions, and bedrock reflection down to 50 m below the ice surface.

Synthetic aperture radar (SAR) data collected over a 2-D synthetic aperture can be processed to focus the illuminated scatterers in the 3-D space, using a number of signal processing techniques generally grouped under the name of SAR tomography (TomoSAR). A fundamental requirement for TomoSAR processing is to have precise knowledge of the platform position along the 2-D synthetic aperture. This requirement is not easily met in the case where the 2-D aperture is formed by collecting different flight lines (i.e., 1-D apertures) in a repeat-pass fashion, which is the typical case of airborne and spaceborne TomoSAR. Subwavelength platform position errors give rise to residual phase screens among different passes, which hinder coherent focusing in the 3-D space. In this paper, we propose a strategy for calibrating repeat-pass tomographic SAR data that allows us to accurately estimate and remove such residual phase screens in the absence of reference targets and prior information about terrain topography and even in the absence of any point- or surface-like target within the illuminated scene. The problem is tackled by observing that multiple flight lines provide enough information to jointly estimate platform and target positions, up to a roto-translation of the coordinate system used for representing the imaged scene. The employment of volumetric scatterers in the calibration process is enabled by the phase linking algorithm, which allows us to represent them as equivalent phase centers. The proposed approach is demonstrated through numerical simulations, in order to validate the results based on the exact knowledge of the simulated scatterers, and using real data from the ESA campaigns AlpTomoSAR, BioSAR 2008, and TropiSAR. A cross-check of the results from simultaneous P- and L-band acquisitions from the TropiSAR data set indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters.

In this paper we propose a new methodology to estimate the absolute Digital Elevation Model (DEM) of an area by radargammetric-like processing of interferometric multi-baseline SAR data from two opposite-side surveys. First, two separate DEMs of the imaged area are obtained from two opposite-side tomographic SAR views. Both the DEMs thus obtained are affected by residual baseline errors. Coregistration of the DEMs is thus performed, so as to correct these errors. This methodology combines the great accuracy of multi-baseline interferometric processing with precise stereo plotting typical of opposite-side radargrammetry, requires no texture matching and no control points and can be applied also in the case of few a-priori information about the site topography.

Climate change and anthropogenic pressures are expected to reduce global freshwater availability and to exacerbate water crises in the near futures. To manage water crisis, the most common path of the past century has been a “hard-path”, based on centralized structural actions, strongly affecting the environment. This work aims at developing novel adaptive water management control strategies, in a multi-stakeholders context, based on soft-path measures. We focus on the direct, data-driven use of exogenous information to improve the systems anticipation capability. Specifically, the value of snow data in informing water resource systems operation is explored using a model free approach. The underline idea is that information on the snow water equivalent (SWE) in the basin may be relevant to manage the reservoir releases. To this aim SWE estimates are retrieved from SAR COSMO-SkyMed X-band images. The approach is demonstrated on snow-rain fed river basin in the Italian Alps: the Lake Como watershed. Preliminary results show the relevance of snow information to the reservoir management as well as the potential for remote sensed products in data-driven optimization.

The objective of this paper is to provide a better understanding of the impact of temporal decorrelation on the tomography phase of the P-band Synthetic Aperture Radar (SAR) BIOMASS mission, 7-th Earth Explorer of the European Space Agency. In this context, in the framework of the Phase A studies of the BIOMASS mission, the airborne TropiSAR 2009 and ground-based TropiScat 2011 experiments were conducted over the site of the tropical forest Paracou, French Guiana. The P-band SAR tomographic data acquired during TropiSAR campaign allowed us to reconstruct 3-D high resolution data, whereas TropiScat experiment provided vertical temporal coherence of the vegetation. These data therefore allow us to generate a BIOMASS P-band SAR data stack that accounts for both the 6 MHz bandwidth limit and temporal decorrelation. To do this, we developed a tomo-graphic simulator, which can combine 3-D high resolution data from TropiSAR and the temporal decorrelation from TropiScat data-sets, to provide the most realistic temporal BIOMASS tomographic data. The resulting tomograms and forest heights were observed to change acceptably as long as the revisit time is 4 days or less. Therefore, the revisit time for the BIOMASS tomographic phase at 3–4 days as proposed should be feasible.

In this paper, we propose a model-based procedure to estimate the accuracy of Sentinel-1 orbit products by the Multi-Squint (MS) phase. The technique exploits the results of single baseline MS analyses collected for each possible master and slave combination in a stack to estimate the absolute orbit error. Accordingly, as first step we state the geometric model of the InSAR phase and the MS phase model as derivative of the In-SAR phase geometric model with respect to the squint angle, then we describe the algorithm to estimate two components of baseline error using the theoretical model. In this paper we focus on the TOPSAR acquisition modes of Sentinel-1 assuming at the most a linear error in the known slave trajectory. In particular, we describe a dedicated methodology to measure baselines accuracy using bursts and swaths overlaps in data acquired by IW and EW acquisition modes. Finally, we suggest a technique to estimate, by a weigthed least-squase inversion, the absolute orbit error of each image in a stack. Experimental results of single and multi-baseline MS analysis obtained on Sentinel-1 data will be displayed.

The objective of this paper is to provide a better understanding of tomographic capabilities in characterization of dense forested areas at P-and L-band. The analysis is carried out on airborne data acquired by ONERA over the site of Paracou, French Guyana, during the ESA campaign TropiSAR. The results shown support the idea that ground- and -volume interactions play a negligible role at L-band, whereas they are significant at P-band. For a dense forest of 30 m and more, there is very weak ground contribution at L-band. The L-band tomographic profile is quite disturbed as compared to the P-band profile in dense tropical forest areas. In this condition, the use of tomographic imaging at L-band in tropical forests appears limited. However, when the forest top height is roughly below 20 m (e.g., in forest regrowth), the tomographic results are expected to be the same as in boreal forests. Whereas P-band tomography allow us to retrieve the whole forest vertical structure, better characterizing of the ground and/or volume scatterings and providing an unique solution in high biomasss ranging from 150-600 t/ha.

In this paper we present results from the tomographic analysis of L-Band SAR data acquired in February/March 2014 over the Mittelbergferner glacier, Austrian Alps, during the ESA campaign AlpTomoSAR. The campaign includes coincident in-situ measurements of snow and ice properties, as well as high-frequency Ground Penetrating Radar (GPR) data acquired over a total length of 18 km. The analyses of three-dimensional TomoSAR data cubes shows the complexity of the glacier sub-surface scattering. Most areas are characterized by surface scattering in proximity of the Lidar surface, plus a complex pattern of in-depth volumetric scattering beneath. Various subsurface features observed in GPR transects at 600 MHz and 200 MHz clearly showed up in TomoSAR sections as well. In particular: firn bodies, crevasses, and even the bedrock down to 50 m below the ice surface.

In this paper we discuss 3D tomographic techniques for processing airborne SAR data acquired from largely irregular trajectories. The discussion is based on the L-Band data-set acquired over the Mittelbergferner glacier in 2014 in the frame of the ESA campaign AlpTomoSAR. Signal focusing is based on Time Domain Back Projection (TDBP), concerning the generation of both 2D SLC data stacks and 3D Tomographic data cubes, as this approach allows to correctly cope with random trajectory deviations, as well as with range and azimuth shifts depending on focusing height. Data Phase Calibration is also considered, in order to recover phase screens due to an imperfect knowledge of flight trajectories.

This paper presents the preliminary results obtained within a research project aimed to assess the feasibility of a system to monitor the immigration flows in the Southern Mediterranean Sea by solely relying on images coming from scientific and commercial satellites, which already operates on a regular basis. “Space Shepherd”, a project funded by Politecnico di Milano, Italy, has the ultimate goal of integrating information coming from a number of satellites to 1) monitor remotely the Southern Mediterranean Sea, 2) detect the presence of possible vessels, 3) identify the migrant vessels and keep the authorities informed, 4) track the vessels and issue warnings in case of danger, 5) support the search and rescue operations. The methodology for scheduling image acquisitions is presented, as well as the algorithms for automatic detection of vessels in both optical and SAR images. The performances of the system are discussed, and its feasibility is assessed.

The objective of this letter is to provide a better understanding of the impact of temporal decorrelation on the tomographic phase of the P-band synthetic aperture radar (SAR) mission BIOMASS, selected as the Seventh Earth Explorer by the European Space Agency. In the context of Phase A BIOMASS activities, the tropical forest site of Paracou, French Guiana, was illuminated at P-band during the airborne campaign TropiSAR 2009 and the ground-based campaign TropiScat 2011. P-band data from TropiSAR were used to generate a high-resolution 3-D reconstruction of the Paracou forest, whereas TropiScat data provided information about temporal correlation considering different time lags and different heights within the vegetation layer. The ensemble of the two datasets were used to generate a synthetic SAR data stack that emulates BIOMASS acquisitions over the Paracou forest site, accounting for BIOMASS geometry and resolution, as well as for the forest temporal decorrelation. Different data stacks were produced by varying the revisit time between two consecutive passes from 1 to 17 days. The resulting vertical structure reconstruction and forest height retrieval were observed to yield valuable results as long as the revisit time is 4 days or less.

The objective of this paper is to provide a better understanding of the capabilities of the BIOMASS tomography concerning the retrieval of forest biomass and height in tropical areas. The analysis presented in this paper is carried out on airborne data acquired by Office National d'Etudes et de Recherches Aérospatiales (ONERA) over the site of Paracou, French Guiana, during the European Space Agency campaign TropiSAR. This high-resolution data set (125-MHz bandwidth) was reprocessed in order to generate a new data stack consistent with BIOMASS as for the bandwidth (6 MHz) and the azimuth resolution (about 12 m). To do this, two different processing approaches have been considered. One approach consisted of degrading the resolution of the airborne data through the linear filtering of raw data, followed by standard SAR processing. The other approach consisted of recovering the 3-D distribution of the scatterers at a high resolution, which was then reprojected onto the BIOMASS geometry. The latter procedure allows us to obtain a data stack that is the most realistic emulation of BIOMASS imaging capabilities. In both approaches, neither ionospheric disturbances nor temporal decorrelation has been considered. The connection to the forest biomass has been examined in both cases by investigating the correlation between the backscatter at different forest heights and the above-ground biomass (AGB) values from in situ data. As expected, the reduction of the system bandwidth to 6 MHz resulted in significant vertical resolution losses compared with the original airborne data. Nevertheless, it was possible to retrieve the forest height to within an accuracy of better than 4 m, whereas the backscattered power at the volume height (30 m above the ground) exhibited a correlation higher than 0.8 with the in situ data and no bias phenomena over the AGB values ranging from 250 to 450 t/ha.

In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case.

The following paper concerns preliminary results from a phenomenological analysis of vessel scattering carried out on Synthetic Aperture Radar Spotlight data. Time-frequency analysis tools have been applied to real data acquired from the German satellite Terrasar X, in order to detect and characterize the different scattering mechanisms contributing to the received signal. The impact and correction of data perturbations due to the motion of the ship are also discussed.

The 7-th ESA Earth Explorer, BIOMASS is a synthetic aperture radar (SAR) which will collect data from employing a multiple baseline orbit during the initial phase of its lifetime. This data can be used for tomographic SAR (TomoSAR) processing resulting in a vertical resolution of about 20 m, sufficient to decompose the backscatter from most tropical forests into two to three layers. A recent study using airborne data from the TropiSAR campaign at the site of Paracou, French Guiana, showed that this information significantly improves the retrieval of forest above-ground biomass (AGB), resulting in an accuracy of about 10% of AGB at a resolution of 1.5-ha. In this paper, we generalize this result, by applying the same algorithm to the Nouragues test site in central French Guiana. This site is characterized by a hilly terrain and an AGB ranging from 150 to 600 t/ha. The relationship between AGB and TomoSAR data at Nouragues was found to be highly similar to the one observed at Paracou. We found that the best correlation between the backscatter signal and AGB is held in the upper canopy layer (i.e. 20-40 m). Cross validation using training plots from Nouragues and validation plots from Paracou, and vice versa, resulted in an accuracy of about 16%-18% of AGB using 1-ha plots. This result suggests that the TomoSAR AGB retrieval method is generalizable to other study sites. In addition we show that, TomoSAR can be used to estimate the canopy height with an error of less than 4 m with forest height ranging from 20 m-40 m.

In this paper we present results relative to the 3D GBSAR surveys acquired in february 2013 on the Austrian Alps as a part of the ESA campaign AlpSAR. The GBSAR was operated at X- and Ku-Band with a bandwidth of 4 GHz and employing a 2D synthetic aperture, resulting in 3D resolution capabilities at a resolution of few centimeters. Images produced at two different sites reveal the presence of multiple layers within the snowpack. The strongest backscatter contributions have been observed to correspond to bottom layers, that dominate the ones from the snow/air interface and the near subsurface. GBSAR data are observed to provide sensitivity to the propagation velocity into the snowpack, as revealed by the apparent depth variation with respect to the incidence angle.

Synthetic aperture radar tomography (TomoSAR) estimates the scene reflectivity along range, azimuth and elevation directions. Even if many works in recent literature deal with this topic, TomoSAR imaging remains a not easy procedure. In this work, the possibility to improve quality of imaging by a priori information is investigated experimentally; in particular we focus on urban scenario where targets of interest are point-like and radiometrically strong. Accordingly, we look for a sparse reflectivity function; this can be obtained minimizing the solution in an arbitrary Lpnorm using the It-eratively Reweighted Least Square (IRLS) algorithm. Based on an experimental comparison among different choices for p, the conclusion drawn is that the usual choice p = 1 is the best trade-off between resolution and robustness to noise. Therefore, L1norm minimization by IRLS has been exploited to perform CS TomoSAR on real data, and we report in this paper first results obtained using COSMO-SKyMed data acquired over an area in Milan, Italy.

The next ESA Earth Explorer Core Mission BIOMASS is envisaged to collect multiple baselines on selected areas during the initial phase of its lifetime. Such data will allow to image the vertical structure of the vegetation layer to within a vertical resolution of about 20 m, sufficient to decompose the backscattered power from a tropical forest into two-three layers. The information provided by tomography has recently been shown to be strictly linked to above ground biomass (AGB) in tropical forest, therefore providing a valuable tool for ABG estimation. The aim of this paper is to present a bird-eye overview of BIOMASS Tomography, along with the main experimental results from airborne campaigns flown during Phase-A BIOMASS activities.

In this letter, we present the results from the ground-based European Space Agency campaign TropiScat, which is aimed at evaluating the temporal coherence at P-band in a tropical forest in all polarizations and at different heights within the vegetation layers. The TropiScat equipment has been operated since October 2011 at the Paracou field station, French Guiana, to continuously produce height-range images of the forest with a temporal sampling of 15 min. The forest temporal behavior can be then captured by analyzing the interferometric coherence between the images gathered at different times, considering time scales on the order of hours, days, and months. The results indicate that the vegetation is likely to undergo a significant motion during day hours due to wind and temperature changes, whereas it appears to be definitively more stable during night hours. This result appears to provide a very useful input to the Biomass Monitoring Mission for Carbon Assessment (BIOMASS), as it suggests that the performance over a tropical forest could be optimized by gathering acquisitions in early morning or night hours. The long-term temporal decorrelation has been then evaluated by considering dawn-dawn acquisitions to minimize the impact of wind gusts and by excluding rainy days in order to not confuse forest and system decorrelation. As a result, the temporal coherence at the ground level was found to stay high at about 0.8 at 27 days, whereas the temporal coherence at the canopy height was found to be about 0.8 at 4 days and about 0.65 at 27 days, indicating coherence sensitivity to height.

The retrieval of above-ground biomass (AGB) in dense tropical forests using synthetic aperture radar (SAR) images is widely recognized as a challenging task. The first difficulty arises from the decrease of sensitivity of the backscattered intensity to biomass at high biomass values, often referred to as the backscatter saturation effect. At P-band, the decrease of sensitivity can occur at biomass values higher than about 300${\rm t~ha}^{-1}$, e.g., those of many dense tropical forests. Another limiting factor is associated with the ground effects, as they can change significantly the magnitude of returns from vegetation–ground interactions. As a consequence, terrain topography or ground moisture status can determine the variations of the observed signal that are not due to forest biomass. A solution to reduce the ground effects is to have access to layers inside the forest canopy where the backscatter from vegetation–ground interactions is not significant. The study presented in this paper is an attempt to overcome the issues outlined above based on direct 3-D imaging of the forest volume, which is possible through multibaseline SAR tomography. In this way, forest biomass can be investigated by considering not only the backscattered power at each slant range and azimuth location but also its vertical distribution. The data analyzed in this paper are from the P-band airborne dataset acquired by Office National d'Études et de Recherches Aérospatiales (ONERA) over French Guiana in 2009, in the frame of the European Space Agency campaign TropiSAR. The dataset is characterized by a favorable baseline distribution, resulting in a vertical resolution less than half the forest height, which made it possible to decompose the vertical distribution of the backscattered power into a number of layers by coherent focusing, i.e., without assuming any prior knowledge about the forest vertical structure. For each layer, the relationship between the backscattered power and forest AGB was then analyzed. As expected, it was found that the power from the bottom layer is very weakly correlated to AGB, whereas the power from a layer at about 30 m above the ground yields the best correlation and sensitivity to AGB in all polarizations, for actual AGB values ranging from 250 to 450${\rm t~ha}^{-1}$. An interpretation of this result is also provided, based on a forest growth model simulation. Finally, the relevance of tomographic technique in P-band spaceborne mission is discussed.

Due to the increased melting of ice sheets over the last decades, monitoring of ice dynamics and structure with remote sensing instruments is of extreme importance to achieve a deeper insight on related environmental issues. The study presented in this paper documents an attempt of mapping ice structure with P-band SAR tomography. First results from ESA IceSAR 2012 campaign carried out in south-west Greenland are presented. It is found that significant penetration in the upper layers of glacial subsurface can be achieved up to an extent of about 20-60 m, conditional on the different type of glaciological zone observed.

We propose an efficient method for the azimuth compression and Atmospheric Phase Screen estimation of Geosynchronous SAR data. The method is based on the iterative processing of sub-apertures of increasing size, allowing to gradually refine the quality of the focused data and of the estimated APS. The whole processing can be easily parallelized. Results over simulated data are shown.

In this paper we present results from the ground-based ESA campaign TropiScat, aimed at evaluating the temporal coherence at P-band in a tropical forest in all polarizations and at different heights within the vegetation layers. The TropiScat equipment has been operated since October 2011 at the Paracou field station, French Guiana, to continuously produce height-range images of the forest below with a temporal sampling of 15 minutes. The forest temporal behaviour can then be captured by analyzing the interferometric coherence between images gathered at different times, considering time scales on the order of hours, days, and months. Temporal coherence at the ground level was found to be higher than 0.8 at 27 days in all polarimetric channels, whereas temporal coherence at canopy height was found to be about 0.8 at 4 days and about 0.65 at 27 days, witnessing coherence sensitivity to height.

This paper proposes and compares different spectral estimation techniques to perform polarimetric 3-D imaging using SAR tomography (POLTOM). Parametric approaches based on the Random Volume over Ground model as well as non parametric techniques are proposed to derive 3-D full second-order polarimetric representations. Their theoretical performance is evaluated over simulated data sets and they are applied to the characterization of forested environments at L and P bands.

The paper debates a novel solution for the longterm monitoring of the system polarimetric quality based on radiometrically and polarimetrically stable targets, herewith named Polarimetric Permanent Scatterers (PPS). The technique is completely scene-based and thus cost effective. It allows, aided by the integration with the available Distributed Target (DT) information, for the relative calibration of the channel imbalance and cross-talk parameters. Their complex time-series information is indeed extracted with respect to the absolute unknown values of an arbitrary image of the stack. The performance achieved on a Radarsat-2 stack show that the accuracy is consistent with that returned by DT techniques. The attention shall be however focused on the fact that the more information can actually be extracted thanks to the proposed monitoring method.

In this paper we present experimental results relative to the vertical structure of a 60 cm snow-pack as sensed with X- and Ku-Band microwaves. The available data are from a Ground Based (GB) SAR campaign carried out by the University of Rennes I in December 2010 at Col de Porte, in the French Alps, in collaboration with Meteo-France. The data have been acquired by moving a VNA along two orthogonal directions, so as to obtain a two dimensional synthetic array. This allowed to focus the signal in the three dimensional space, thus providing a direct imaging of the vertical structure of the snow-pack at a resolution of few centimeters. Results revealed the presence of strong backscattering contributions from beneath the snow layer, that appear to be linked to the presence of an ice layer.

In this paper we propose a strategy for phase calibrating repeat-pass Synthetic Aperture Radar (SAR) data for tomographic applications. The problem is tackled by observing that multi-baseline data provide equations enough to jointly estimate aircraft and target positions, up to a rototranslation of the coordinate system used for representing the imaged scene. Such a rototranslation is shown to correspond to the forward operator null space, which can be accounted for in order to project the results in the desired coordinate frame. Volumetric scatterers are treated by exploiting the Phase Linking algorithm, which allows to represent them as equivalent phase centers. Results are shown from synthetic data and real SAR data acquired over snow and ice.

In this work, a numerical method optimizer for SAR polarimetric calibration is proposed. The method makes use of the information provided by a Distributed Target and a Corner Reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday Rotation. The different order of magnitude of cross-talks and Faraday Rotation is exploited to overcome the intrinsic ambiguity related to the problem. Tests have been conducted both on simulated data, confirming the ability of the proposed method to provide realistic estimation of the distortion parameters, even in case of low quality Corner Reflector.

In this paper we discuss the design concepts and preliminary results relating to the European Space Agency's ground-based campaign TropiScat, whose main goal is to evaluate temporal coherence at P-band in a tropical forest in quad-polarization, considering temporal lags ranging from hours to months and at different heights within the vegetation layer. The experiment has been successfully set up and operated since October 2011 at the Paracou field station, French Guiana, where the equipment was installed on top of the 55-m high Guyaflux Tower to illuminate the forest below. The system consists of a vector network analyzer connected to 20 antennas through a switchbox, which allows the use of any of them either as a transmitter or as a receiver. Vertical imaging and fully polarimetric capabilities are achieved by operating the 20 antennas in a multistatic fashion, resulting in an equivalent monostatic array consisting of 15 phase centers displaced along the vertical direction in each polarization. Such a design allows unambiguous imaging of the vegetation while yielding a minimum distance between nearby antennas on the order of 0.8 m, so as to minimize coupling effects. The equipment allows the gathering of signals with the tomographic array within a few minutes, resulting in the possibility to produce a tomographic image of the forest with a temporal sampling of 15 min. System calibration and validation was performed by employing a 2-m trihedral reflector and a rotating dihedral reflector. This allowed the evaluation of the system pulse response in all polarizations and also assessment of the extent of tower motions. As a result, tomographic images have been generated from 500 (P-band) to 900 MHz in all polarizations. Results from real data acquired in Fall 2011 confirm the feasibility of carrying out reliable coherence measurements for the whole duration of the campaign.

In this paper, we revise the relative radiometric calibration of synthetic-aperture-radar stacks which exploits natural persistent scatterers (PSs). We introduce a new model to estimate a slight error in the sensor pointing in elevation and a new coherent method that makes use of phases evaluated by averaging the complex data on the local window. We show that the proposed approach outperforms the conventional one, as it is mostly insensitive to the “differential” biasing that affects the noncoherent permanent scatterer calibration (PScal). Results from processing COnstellation of small Satellites for the Mediterranean basin Observation (COSMO)-SkyMed and European Remote Sensing (ERS) satellites stacks are presented.

This paper aims at characterizing the scattering mechanisms occurring at the ground level in a tropical forest illuminated by a P-band synthetic aperture radar (SAR). The analysis is carried out based on the multibaseline, fully polarimetric, data set collected by ONERA over Paracou, French Guyana, in the frame of the European space agency campaign TropiSAR. The favorable baseline distribution of this data set results in the possibility of removing most contributions from the vegetation layer by tomographic techniques, thus allowing the generation of a new fully polarimetric single look complex SAR image relative to scattering contributions from the ground level only. Such a ground layer image is then analyzed by considering the variation of its polarimetric signature with respect to terrain local slope and Radar look angle. Two major conclusions are drawn: 1) double bounce scattering from trunk-ground interactions is observed to be the dominant scattering mechanism at the ground level on flat terrains, whereas it rapidly tends to vanish as the topographic slope increases, and 2) the characteristic parameter that rules trunk-ground scattering is not the tree height, but rather the available free path facing the tree, as a result of the presence of nearby trees, undulating topography, or understory preventing double bounce scattering from taking place whenever the ground bounce occurs too far away from the considered tree. The mean free path length resulting from the analysis of this data-set is found to be L ≅ 7 m. Finally, we discuss how the concept of free path length can be accounted for in simple terms by assuming an equivalent extinction model characterized by a variation along the horizontal dimension.

The retrieval of above-ground biomass in dense tropical forests using Synthetic Aperture Radar (SAR) images is widely recognized as a challenging task, because of the backscatter saturation effect at high biomass values and the ground topography effect. The study presented in this paper is an attempt to overcome these issues based on direct three-dimensional imaging of the forest volume, which is possible through multi-baseline SAR tomography. In this way, forest biomass can be investigated by considering not only the backscattered power at each slant range, azimuth location, but also its vertical distribution. It was found that the power from the a layer at 30m ± 10m above the ground yields the best correlation and best sensitivity with forest biomass in all polarizations, for biomass ranging from 250 to 450 tons/ha.

In this paper we present preliminary results from the ground-based ESA campaign TropiScat, aimed at evaluating the temporal coherence at P-band in a tropical forest in quad-polarization and at different heights within the vegetation layer. The TropiScat equipment allows to gather the signal with a multistatic array within few minutes, resulting in the possibility to produce a tomographic image of the forest with a temporal sampling of 15 minutes. Concerning short term temporal decorrelation, the most relevant phenomenon is the coherence drop during daytime, due to the action of wind moving the forest canopy. This result appears to provide a very useful input concerning the BIOMASS mission, as it suggests that performance over tropical forest could be optimized by gathering acquisitions in the early morning or night hours. A diurnal motion along the vertical direction is observed to characterize the forest phase center. Studies are being carried out to evaluate whether this variation can be imputed to forest evapotranspiration phenomena.

The paper discusses methods for radiometric calibration of repeat-pass interferometric SAR stacks based on Persistent Scatterers. Coherent and non-coherent approaches for the estimation of the radiometric gain are compared. Furthermore, an estimator of the beam pointing in elevation in proposed. Evaluation of performances is carried out basing on both simulated and COSMO-SKYMED data.

In this paper we discuss a preliminary design for a constellation of geosynchronous (GEO) Synthetic Aperture Radars (SAR). The key design concept is to employ one or more pairs of closely-spaced twin receivers flown onboard GEO minisatellites moving with a velocity of few meters per second with respect to the Earth's surface, so as to form a synthetic aperture on the order of few tenths of kilometers twice a day. The employement of closely-spaced receivers would enable the estimation of the temporal gradient of the tropospheric delay via along track Interferometry, resulting in the possibility to coherently integrate the signal over an aperture time on the order of hours. As a result an area as wide as one thousand kilometers could be imaged while providing: i) continuous temporal coverage at coarse resolution (hundreds of meters); ii) high resolution (few meters) imaging and interferometric capabilities two or more times a day by integrating the signal over few hours, thus ensuring high SNR performance (for stable targets) with a transmitted power comparable to currently operated spaceborne SARs.

This paper deals with a radar ground experiment dedicated to tropical forest backscattering at P band. With polarimetric and tomographic capabilities, this system is able to provide long-term radar data over a dense tropical forest. These data will be use to improve our comprehension of backscattering mechanisms and their evolution over long periods.

This paper aims at characterizing the scattering mechanisms occurring at the ground level in a tropical forest illuminated by a P-Band SAR. The analyzed data set is the one collected by ONERA over Paracou, French Guyana, in the frame of the ESA campaign TropiSAR. The favorable baseline distribution of this data set results in the possibility to remove most contributions from the vegetation layer by tomographic techniques, thus allowing a direct investigation of ground scattering. Two major conclusions are drawn: i) double bounce scattering from trunk-ground interactions is observed to be the dominant scattering mechanism at the ground level on flat terrains, whereas it rapidly tend to vanish as the topographic slope increases; ii) the characteristic parameter that rules trunk-ground scattering is not the tree height, but rather the available free path facing the tree, as a result of the presence of nearby trees or understory preventing double bounce scattering from taking place whenever the ground bounce occurs too far away from the considered tree.

The aim of this letter is to discuss recent results from the tomographic analysis of the P-band synthetic aperture radar multibaseline data set acquired by ONERA over French Guyana, in the frame of the European Space Agency campaign TropiSAR. Such a data set is characterized by a vertical resolution of about 20 m, whereas forest height ranges from 20 to 40 m. These features make it possible to map the 3-D distribution of the scene complex reflectivity in up to three independent layers by coherent focusing, i.e., without assuming any physical model or employing superresolution techniques. The most relevant features within the observed results are the presence of dihedral-like scattering in the ground layer, which is hardly noticeable in the original single-look complex data, and the substantial invariance of the innermost forest layer to topographic slopes.

We propose a novel method to select long-term coherent targets from a set of repeated-pass interferometric acquisitions. The major assumption is that targets are so close together to share the same optical path. This leads to an efficient singular-value-decomposition-based estimator of the targets' phase and, then, to PS detection. The estimated phase can be used to define the PS coherence for each image. Being sensitive to acquisition and processing artifacts, the PS coherence is a valuable tool for quality assessment of the interferometric stack. Results are shown with real data sets in both single and full polarizations.

Longer wavelength synthetic aperture radars (SARs) are precious in the remote sensing of forested areas, being sensitive to contributions from the whole vegetation layer and from the ground below. The electromagnetic properties of such contributions are retrieved from multipolarimetric acquisitions, whereas their vertical structure is retrieved from multibaseline acquisitions through tomographic imaging. Combining baseline and polarization diversity provides most information, allowing the decomposition of the SAR signal into ground- and volume-only contributions. A formal treatment of this problem is provided with the algebraic synthesis technique, which extends the concepts of PolInSAR. The decomposition, however, is shown to be ambiguous in that different solutions are equally consistent with the data. The main goal of this paper is to discuss this topic in light of the experimental results from a tomographic and polarimetric analysis of the boreal forest within the Krycklan River catchment, Northern Sweden, investigated at P- and L-bands during the ESA campaign BioSAR 2008. Different solutions to the decomposition problem will be discussed by examining the corresponding vertical structures accessible through tomographic techniques. Elements are shown supporting the idea that ground-volume interactions play a nonnegligible role at P-band, and a solution is proposed to isolate contributions from direct volume backscattering. The retrieval of forest top height is discussed as well, leading to the conclusion that such parameter is robust against erroneous choices in the identification of volume-only contributions, thus corroborating the PolInSAR approach for the analysis of single-baseline data.

This paper deals with a ground experiment and its modelization, related to the future spaceborne BIOMASS mission for global forest biomass estimation.

We propose a robust and reasonably fast approach to provide phase estimation and stable target (Persistent Scatterers, PS) detection from a set of repeated pass interferometric acquisitions. The major assumption is that, locally, the PS phase model is decomposed into the separable product of the intrinsic target phase times the optical path, that is common to all the targets in the estimation window. The Singular Value Decomposition (SVD) is exploited to get at one time a fast estimate of the local phase and the detection of stable targets. The estimated phases are then exploited to measure the PS coherence over the whole image or in image blocks. Being sensible to acquisition and processing artifacts, the PS coherence is a valuable tool for automatic image quality assessment. Results are shown with real datasets in both single and full polarization.

The paper proposes a calibration technique based on Permanent Scatterers (PS) for the full-pol L-band and future P-band spaceborne SAR systems. It will be shown how both a radiometric and polarimetric monitoring of the system parameters can be carried out by exploiting the stable targets in the scene. The procedure aims to estimate the overrall system gain, the channel imbalances, and the Faraday rotation angles which must be accounted at such frequencies. The performance achievable by the technique is investigated with concern to the number of images and PSs which shall be supplied to the algorithm in order to meet the desired accuracy requirements.

In this paper we discuss some relevant features observed concerning wave penetration at P-band in boreal and tropical forests. The discussion will be based on results obtained from the multi-polarimetric and multi-baseline data-sets relative to the forest sites within the Krycklan river catchment, Sweden, and the area of Paracou in French Guyana, collected in the frame of the ESA campaign BioSAR 2008 and TropiSAR 2009, respectively. The analysis is carried out by exploiting the SAR tomography technique, which allows to separate backscattering contributions from different heights within the vegetation layer. One first relevant result is relative to the difference between the vertical distribution of the backscattered power in the two investigated test sites. In the boreal forest site the most relevant scattering contributions are observed at the ground level, not only in copolarized channels but also in HV, whereas in the tropical forest the presence of scattering from the ground is poorer and the vegetation volume is well visible. Most relevant features of the investigated tropical forest site are those relative to the dependency of the vertical backscattering distribution with respect to topographic slope and forest biomass. In particular, the innermost forest layer is observed to be substantially invariant to topographic slopes, whereas the backscattered power at 30 m above the ground is observed to yield the best connection with forest biomass, resulting, in this case, in a correlation factor of 0.82 with respect to in-situ measurements at 125 m spatial resolution.

In this paper we examine two different approaches to the estimation of ground and volume interferometric coherences from single and multi-baseline PolInSAR data. One approach, largely retained in literature, is to force the hypothesis that, in each interferogram, the variation of the interferometric coherence with polarization gives rise to a line in the complex plane. The other approach is to process all interferograms jointly by assuming that the data covariance matrix is structured as a Sum of Kronecker Products (SKP). Those two approaches are compared from the algebraic and statistical point of view. Results from simulations show that joint processing all avail able interferograms improves coherence estimation, even though a careful implementation is required to avoid underestimation of coherences close to one in magnitude.

This paper deals with the estimation of terrain topography from multipass synthetic aperture radar (SAR) interferometry (InSAR), focusing on the case where variation of the system geometry within the imaged swath is relevant. A typical case is represented by airborne multipass interferometric campaigns where, due to the closeness between the radar sensor and the targets, the incidence-angle sensitivity undergoes a dramatic increase with respect to the spaceborne case, resulting in a high spatial variability of the normal baselines. The space-varying nature of the system geometry gives rise to a major issue in multipass InSAR analyses in that it prevents from compensating for the presence of interferogram phase offsets by simply phase locking the data stack to a reference point, therefore hindering the retrieval of terrain topography. To cope with this issue properly, we propose a novel approach that exploits the algebraic properties of the problem. Such an approach allows casting the problem in terms of identification of a null-space component for terrain topography after which both topography and the interferogram phase offsets are quickly obtained without exploiting calibration points. Experimental results are shown based on a P-band data set acquired by the Experimental SAR (E-SAR) airborne system, operated by the German Aerospace Center (DLR), in the framework of the European Space Agency (ESA) campaign BIOSAR 2008.

This work deals with the estimation of terrain topography from multi-pass Synthetic Aperture Radar (SAR) interferometry (InSAR), focusing on the case where the variation of the system geometry within the imaged swath is relevant, as in airborne multi-pass interferometric campaigns. The space varying nature of the system geometry gives rise to a major issue in multi-pass InSAR analyses, in that it prevents from compensating for the presence of interferogram phase offsets by simply phase locking the data stack to a reference point, therefore hindering the retrieval of terrain topography. To cope with this issue properly we propose a novel approach that exploits the algebraic properties of the problem. Such an approach allows to cast the problem in terms of identification of a null space component for terrain topography, after which both topography and the interferogram phase offsets are quickly obtained without exploiting calibration points.

In this paper we address three topics related to SAR Tomography of forest scenarios at P-Band. In first place we discuss the role of pulse bandwidth, which is shown to play a critical role as for the capability of the Tomographic system to separate ground and canopy contributions. Accordingly, vertical resolution depends not only on baseline aperture, but also on pulse bandwidth. Another factor to be accounted for is phase calibration, as the quality of the vertical focusing carried out by SAR Tomography is strictly related to the condition that phase contributions due to platform motion or atmospheric propagation are properly compensated for. Finally, multiple scattering phenomena are likely to occur at longer wavelengths, resulting in Tomographic techniques not being suffice for the aim of discriminating ground and volume scattering. The three points above are here discussed in light of the results achieved in the framework of the ESA campaign BioSAR 2008. The analysis has been carried out by exploiting the Algebraic Synthesis technique, which provides a theoretical framework to decompose the SAR signal into ground-only and volume-only contributions. Ground-only contributions provide an easy and viable way to phase calibrate the data stack. Volume-only contributions, if correctly identified, allow a direct Tomographic imaging of the vegetation layer. The impact of pulse bandwidth is tackled by assuming a Common Band Filtering approach, which results in a vertical resolution improvement by a factor 2.

SAR data gathered from forested areas collect contributions coming from the vegetation layer, from the ground below and from other scattering mechanisms (SMs). Multi-baseline data allow a tomographic analysis thus retrieving information about the vertical structure of the target. Multi-polarimetric acquisitions enrich the data, providing ways to identify the targets basing on their electromagnetic properties. The joint exploitation of multi-polarimetric and multi-baseline data suggests the possibility of linking the estimation of the vertical structure of different SMs with their polarimetric signature. A formal framework in which this task can be accomplished is provided by the Algebraic Synthesis (AS) technique, which extends the concepts within PolInSAR through the assumption of the Sum of Kronecker Products (SKP) structure. By assuming the presence of two SMs (for example ground and volume scattering), the SKP assumption leads to a cross dependence between the polarimetric and interferometric coherences, in that ground structure is shown to be related to volume polarimetry, and dually volume structure is shown to be related to ground polarimetry. The aim of this paper is to investigate the implications of this cross relation. Experimental results will be shown basing on a data-set of multi-polarimetric and multi-baseline SAR images at P-band acquired by DLR's E-SAR over the Krycklan catchment, in northern Sweden, in the framework of the ESA campaign BioSAR 2008.

This letter focuses on estimating the local fringe frequency of the interferometric phase, under the hypothesis of superficial scattering. Starting from the formulation of the maximum-likelihood estimator, a new simplified estimator is derived. Due to computational efficiency and robustness versus model errors, the resulting estimator is suited for large data processing in the presence of model uncertainty. Furthermore, such an estimator can be straightforwardly extended to the multibaseline case, resulting in the possibility to estimate the terrain slope with great accuracy. An application to real data is presented, based on a multibaseline ENVISAT data set.

We propose a calibration method suitable for a set of repeated synthetic aperture radar (SAR) acquisitions that uses both absolute calibrated devices (such as corner reflectors) and stable targets identified in the scene [the permanent scatterers (PSs)]. Precisely, the role of the PS is to extend the initial calibration sequence by monitoring the radiometric stability of the system throughout the whole mission life span. At a first step, this paper approaches the problem of PS-based normalization by an iterative maximum-likelihood method that exploits the stack of complex interferometric SAR images. Two solutions are given based on different assumptions on the PS phases. As a second step, the merging of these estimates with the available calibration information is discussed. Results achieved by experimental acquisitions are shown in two different SAR systems: 1) a C-band spaceborne SAR and 2) a Ku-band ground-based SAR.

In this paper, a technique is described for the tomographic characterization of forested areas through multiple synthetic aperture radar (SAR) observations, based on either single or multipolarimetric acquisitions. This technique is based on the idea of characterizing the Fourier spectrum of the multibaseline data as being constituted by two effective scattering centers displaced along the vertical direction, plus the associated decorrelation terms. As a result, SAR tomography will be formulated as the problem of detecting the number of scattering centers within the resolution cell, estimating the parameters that describe their spatial structure, and evaluating the associated backscattered powers. Parameter estimation is carried out through the covariance matching estimation technique, which provides an asymptotically optimal solution. The results of an experiment performed on a real P-band multibaseline fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported.

This paper is meant to present a statistical analysis of the role of propagation disturbances (PDs), such as those due to atmospheric disturbances or to residual platform motion, in multibaseline synthetic aperture radar (SAR) interferometry (InSAR) and tomography (T-SAR) applications. The analysis will consider both pointlike and distributed targets in such a way as to cover all the cases that are relevant in the applications. In order to provide a tool for the evaluation of the impact of PDs on the analysis of an arbitrary scenario, a definition of signal-to-noise ratio (SNR) will be introduced that accounts for both the presence of PDs and the characteristics of the imaged scene. In the case of pointlike targets, it will be shown that such definition of SNR allows reusing well known results following after the Neyman–Pearson theory, thus providing a straightforward tool to asses phase-stability requirements for the detection and localization of multiple pointlike targets. In the case of distributed targets, instead, it will be provided a detailed analysis of the random fluctuations of the reconstructed scene as a function of the extent of the PDs, of the vertical structure of the imaged scene, and of the number of looks that are employed. Results from Monte Carlo simulations will be presented that fully support the theoretical developments within this paper. The most relevant conclusion of this paper is that the impact of PDs is more severe in the case where the imaged scene is characterized by a complex vertical structure or when multiple pointlike targets are present. As a consequence, it follows that the T-SAR analyses require either a higher phase stability or a more accurate phase calibration with respect to InSAR analyses. Finally, an example of phase-stability analysis and phase calibration of a real data set will be shown, based on a P-band data set relative to the forest site of Remningstorp, Sweden.

Synthetic Aperture Radar (SAR) and Sonar (SAS) systems provide high resolution reflectivity maps of the imaged scene by coherently combining the echoes collected along a virtual array of receivers. A peculiarity of SAS systems is that the echoes are often collected by moving a short real array of hydrophones to avoid range ambiguity. In this paper we present a modification of the standard wavenumber focusing algorithm widely used in SAR data processing to make it suitable for focusing bi-static SAS data. An autofocusing technique is then exploited to estimate and compensate for the deviation of the platform trajectory from the rectilinear one.

In this paper, an algebraic methodology is described for the separation of ground and volume contributions basing on multi-baseline and multi-polarimetric acquisitions. As a result, a new general procedure is defined that encompasses single-baseline PolInSAR as a special case, and allows to proceed to ground/volume separation not only through model based approaches, but also through model free and hybrid approaches. Furthermore, it will be shown that such a methodology yields the best solution in the Least Square sense.

In this paper, a new methodology is proposed for the analysis of forested areas basing on multipolarimetric multibaseline synthetic aperture radar (SAR) surveys. Such a methodology is based on three hypotheses: 1) statistical uncorrelation of the different scattering mechanisms (SMs), such as ground, volume, and ground-trunk scattering; 2) independence of volumetric and temporal coherence losses of each SM on the choice of the polarimetric channel; and 3) invariance (up to a scale factor) of the average polarimetric signature of each SM with respect to the choice of the track. Under these hypotheses, the data covariance matrix can be expressed as a Sum of Kronecker Products, after which it follows that K SMs are uniquely identified by K (K - 1) real numbers. This result provides the basis to perform SM separation by employing not only model-based approaches, generally retained in literature but also model-free and hybrid approaches, while yielding the best Least Square solution given the hypothesis of K SMs. It will be shown that this approach to SM separation is consistent with the inversion procedures usually exploited in single-baseline polarimetric SAR interferometry. Experimental validation of this methodology is provided on the basis of the P-band data set relative to the forest site of Remningstorp, Sweden, acquired by German Aerospace Center's E-SAR airborne system in the framework of the European Space Agency campaign BioSAR.

This paper focuses on the generation of physically valid views from two or more uncalibrated images acquired by standard cameras. The problem is faced without trying to yield a three dimensional reconstruction of the imaged scene, which would be unfeasible without the exact knowledge of the positions of the cameras in the Euclidean frame where the scene is to be described. Instead, starting from the previous works of Shashua and Navab on relative affine structure (1996) and the article of Fusiello on views synthesis from uncalibrated views (2007) we propose a novel approach that does not require the presence of a plane at infinity to define the homography between two views but merely the parallelism between couples of planes. This allows our approach to be applied to numerous scenes where two parallel planes can be defined (indoor scenes, straight streets and avenues). Experiments with synthetic images illustrate the approach.

In this paper a technique is described for the tomographic characterization of forested areas through multiple SAR observations. This technique is based on a model of the second order statistics of the multi baseline, multi polarimetric, data which accounts for the presence of multiple distributed targets within the system resolution cell. The results of an experiment performed on a real P-band, multi-baseline, fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported. Such results show the feasibility of performing a model based tomographic analysis of forests, resulting in a characterization of both the ground and the canopy in terms of elevation, spatial structure, and scattered power.

This paper focuses on multiimage synthetic aperture radar interferometry (InSAR) in the presence of distributed scatterers, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step, we estimate the interferometric phases from the data, whereas in the second step, we use these phases to retrieve the physical parameters of interest, such as line-of-sight (LOS) displacement and residual topography. In both steps, we make the hypothesis that target statistics are at least approximately known. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and topography. Results achieved from Monte Carlo simulations and a set of repeated pass ENVISAT images are shown.

This paper focuses on multi-pass spaceborne synthetic aperture radar interferometry (InSAR) in presence of distributed scattering, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step we estimate the interferometric phases from the data, while in the second step we use these phases to retrieve the physical parameters of interest, such as LOS displacement and residual topography. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and DEM. Results achieved from Monte-Carlo simulations and a set of repeated pass ENVISAT images are shown.

This letter focuses on the performance achievable by spaceborne synthetic aperture radar interferometry (InSAR) in the estimation of line-of-sight crustal deformations from acquisitions over a distributed scatterer. Our model is suited for exploiting the hybrid Cramer-Rao bound (HCRB), where the unknowns are both deterministic parameters and stochastic variables. We take into account both target decorrelation and atmospheric phase screen (APS). This approach leads to a viable evaluation of InSAR performance as a function of system configuration, target decorrelation, and APS variance.

This paper introduces a novel ML based approach to channel identification for time variant SIMO (single input multiple output) systems fed by a stochastic process. We focus on the particular case where the unknowns are represented by the channels phases, that find applications in radar interferometry. Starting from the rigorous formulation of the ML estimator, we derive an approximation that makes use of mixers and FIR filters only. The computational efficiency and the robustness versus model errors of the resulting estimator make it suitable for its implementation is an adaptive framework. An application in topography reconstruction from real SAR (synthetic aperture radar) data is presented