Simultaneous polarimetric radars (SPRs) are powerful tools for measuring the polarization scattering matrix of targets in a single pulse. However, a major challenge associated with SPRs is the design of orthogonal waveforms that can effectively minimize the interference arising from simultaneous transmission and reception. Currently, frequency modulation (FM) and phase-coded modulation are the most commonly used signal structures. However, these signal structures suffer from certain limitations that necessitate the development of new orthogonal waveforms that are both well-suited to high-power transmitters and maximally free in design. This article proposes an approach that leverages polyphase-coded FM waveforms to design orthogonal structures that combine the benefits of FM and phase-coded waveforms. A mathematical model for designing such waveforms is established considering a matched filter at the receiver. The model unifies the parameters of orthogonality and sidelobe level into a fraction expressed in terms of the sidelobe integral level, main-lobe integral level of autocorrelation functions, and entire-lobe integral level of cross correlation functions. This fraction accurately characterizes the orthogonality and sidelobe level of a pair of waveforms. The optimal waveform group can be obtained using a binary gradient descent algorithm, with peak sidelobe levels and isolation levels simultaneously approaching −30 dB. Finally, this article describes the implementation of the proposed orthogonal waveforms on hardware and verifies their performance by presenting experimental results that confirm the effectiveness of the proposed method.

Limited by the achievable pulse peak power, narrowing the transmitted pulsewidth to improve the spatial resolution would reduce the output power of wind Lidar, thereby decreasing the detection range. To solve this dilemma, a time-division multifrequency wind Lidar (TDMWL) is proposed with a long pulse duration consisting of consecutive multiple subpulses at different frequencies. Different detection ranges can be separated by different downconverted frequencies. The accumulation of multifrequency spectra enlarges the output power, while the width of the subpulse determines the spatial resolution. In the experiment, with a subpulse width of 200 ns, the detection range is increased from 750 to above 1200 m by accumulating six frequencies, proving the potential of TDMWL in measuring longer range without deteriorating the spatial resolution.

Highly variable polarimetric signatures caused by complex structures in built-up areas make interpretation of these scattering behaviors intractable for PolSAR remote sensing. This paper proposes a fine polarimetric decomposition method and derives several products to finely simulate the scattering mechanisms of urban buildings, thus fulfilling its use for effective surveillance. First, through theoretically establishing the roll-invariant condition for a completely general scatterer, a roll-invariant cross polarization (RICP) scattering model is constructed, which characterizes the cross polarization scattering in the manner of planar structure distribution. Second, by designing a root-discriminant-based parameter inversion strategy, a fine seven-component decomposition is proposed, which achieves the complete physical interpretation of matrix elements and reasonable inversion of model parameters. Third, by analyzing the external and internal scattering difference, the derivative products, i.e., scattering contribution synthesizers are derived for built-up area monitoring. Experimental results derived from real PolSAR data confirm the superiority and effectiveness of the constructed descriptors on the one hand. On the other hand, the extensibility of fine polarimetric decomposition in specific remote sensing is also explicitly demonstrated.

Without phase information of the measured field data, the design complexity of the observation equipment can be greatly simplified. In the meantime, the phaseless data inverse scattering problems counter more serious nonlinearity and ill-posedness compared to the full data ones. In this article, a multifrequency cross-correlated contrast source inversion (CSI) method using phaseless measurements of the total fields (referred to as PD-CC-CSI) is proposed. By introducing the cross-correlated error term to the cost functional, PD-CC-CSI shows better robustness against data noise and challenges in more complicated inversion scenarios. Inverted results with transversal magnetic (TM) polarized synthetic and experimental data demonstrate the advantages of PD-CC-CSI in comparison to the phaseless data CSI (PD-CSI) method and its variant PD-MR-CSI. In addition, an empirical approach has been proposed to effectively determine the optimal inverted results. Since a fast algorithm can be straightforwardly applied, phaseless inversion with multifrequency data can be done within a few minutes.

Sequence set design with good correlation properties and Doppler tolerance has been a classic and important problem in many multichannel systems, including but not limited to the multiple-input multiple-output (MIMO) and simultaneous polarimetric radar systems. In this article, we first consider the problem of jointly designing Doppler resilient unimodular sequences and receiving filters to minimize the metric weighted integrated sidelobe level (WISL), which can be used to construct sequence sets with “thumbtack” co-channel and zero cross-channel ambiguity functions (AFs). To control the signal-to-noise ratio (SNR) loss caused by the mismatched filter, a peak constraint function is added to the objective function based on the penalty function method. An algorithm based on the alternatively iterative scheme and general majorization-minimization (MM) method is developed to tackle the constrained joint design problem. Moreover, the proposed algorithm is then extended to optimize the${l_{p}}$-norm of sidelobes of AFs, which gives a way to optimize the weighted peak sidelobe level (WPSL) metric. Due to the use of the fast Fourier transform (FFT) algorithm and a general acceleration scheme, the proposed algorithm can be realized efficiently. A number of simulations are provided to demonstrate the excellent performance of the proposed sequence set synthesis algorithms. Besides, an application of using the designed Doppler resilient sequence set on the simultaneous polarimetric radar to detect multiple moving targets in a strong clutter scene is given via simulation, which further verifies the practicability of the proposed algorithm.

It is quite challenging for conventional estimators to extract the radial wind velocities from the raw spectrum data of coherent Doppler wind Lidar (CDWL) at very low signal-to-noise ratios (SNR). This work proposes a new wind velocity estimation method based on the constraints from neighboring wind profiles, which can effectively and robustly extend the reliable detection range of CDWL. Considering the spatial continuity of the wind field, priori information from the velocity probability distributions in previous range bins is utilized to reshape the contaminated spectrum of the current range bin. The influences of different preceding range bins are weighted by their overlapping ratios to the contaminated range bin. Iterations are carried out when computing the variance of the Gaussian-shaped probability, which can preserve the wind field details while removing the parameter dependence in practical applications. The method is verified theoretically in simulated atmosphere echoes as well as experimentally in our self-developed dual-frequency pulsed CDWL system. The first results show that reasonable estimates can be obtained in places far beyond the previous detection boundary provided by conventional estimators.

For the first time, a correlation-free coding technique is demonstrated for improving the detection range of coherent Doppler wind Lidar (CDWL) while roughly maintaining the spatial resolution of single-bit duration. Based on the probing pulses modulated by the improved simplex codes (ISCs), backscattered echoes can be considered as the linear superposition of the Lidar responses, each of which corresponds to different detection locations. Then, the Doppler spectra/wind profile approaching the spatial resolution of a single-bit duration can be recovered after decoding, time delay compensation and accumulation. In contrast to those coding techniques that rely on correlation, the proposed method can be unaffected by the unequal amplitudes of coded bits that are stable between pulses. Theoretically, in simulated atmospheric echoes, it is confirmed that the degraded spatial resolution caused by wide overall emitting pulses can be mitigated while the reliable detection range can be improved. Additionally, experimentally constructed coding CDWLs using 9, 16, 32, and 64-bit ISCs show improvements in detection range that are consistent with the theory.

Compared to the steady-state part of the extended target echo, few scholars have paid enough attention to the echo establishment and disappearance part. They contain abundant target information, but have not been fully explored and utilized. Since the pulse duration of both parts is typically short, they can be considered as instantaneous processes. Polarization is an inherent property of electromagnetic waves, which can bring information gain to the analysis of the echo instantaneous part. The objective of this study is to utilize the instantaneous polarization response (IPR) of the echo to achieve super-resolution for two targets with different polarization scattering characteristics. It is analyzed that when two target echoes are “equal-amplitude and opposite-phase", echo decoupling can be achieved, which is the precondition for achieving range super-resolution. While making full use of the polarization information is instrumental in achieving the echo with “equal-amplitude and opposite-phase". A trihedral and a dihedral are selected to verify the effectiveness of the proposed method. Multiple sets of measured data show that the two target echoes do have the instantaneous part. When the signal-to-noise ratio (SNR) of the echo data is about 6-7dB, the range super-resolution and range estimation of the two targets are achieved by using the edge threshold detector.

Manmade-target three-dimensional (3D) reconstruction is an attractive topic and also a challenge in radar imaging field. The factorization based 3D reconstruction algorithm using multi-view radar images provides a way without extra configuration requirements. The precondition of it is that the reconstructed points' positions are retrievable in all images, but it is hard to be satisfied in practice due to the points loss problem caused by occlusion and scattering variation during view change. The points loss problem reduces the reconstructed points and weaken the details. We propose a modi-fied manmade-target 3D reconstruction algorithm. Firstly, we calculate homography matrix after feature matching of each adjacent image pair and improve its accuracy through non-linear optimization. Then, we put forward a track generation algorithm under the guidance of the homography matrix to estimate strong points' positions in each image and a track filter to refine the estimation. Finally, we achieve the 3D coordinates through the orthographic factorization method. The measured data processing results demonstrate the validity and the reconstruction quality improvement of the proposed method.

Highly variable wind fields (HWFs), which usually have drastically changing velocities over time, can seriously impact aviation safety, wind energy assessment, and so on. A recently proposed deep learning method can well predict the wind fields in ordinary cases, but its performance deteriorates when HWFs are involved. In this letter, a nowcasting method taking into account the impact of HWFs is proposed. First, standard deviations (SDs) of the lidar observations within a time interval are used to identify highly variable events. Second, a loss function weighted by the SDs is adopted to train the nowcasting neural network. Additionally, a new dimensionless metric is introduced to quantitatively measure the nowcasting performance with emphasis on HWFs. Experimental results demonstrate that the weighted loss function can efficiently improve the nowcasting performance on HWFs such as the initiation and dissipation processes of wind shear. Compared with the original nowcasting method, the network with the weighted loss function can reduce the nowcasting errors by an improvement of more than 15.2% in terms of the new metric.

The realistic false targets caused by interrupted sampling repeater jamming (ISRJ) can mask the real target, leading to the failure of radar target detection. In this letter, a method based on jointly designing complementary sequences and receiving filters under the signal-to-noise ratio loss constraint is proposed to suppress ISRJ. A gradient-based nonlinear programming solver and the Lagrange multiplier method are used to optimize the sequences and filters alternately. Numerical results show that the proposed method can generate sequences and receiving filters with good correlation properties and anti-ISRJ performance.

Complete complementary sequence (CCS) design has become an important topic in recent years due to its theoretically ideal zero sidelobe performance. However, the main obstacle for the widespread use of the CCS is its sensitivity to the Doppler shift. In this letter, a method for constructing the CCS with the desired matrix-valued ambiguity functions under a peak-to-average-power ratio (PAR) and an energy constraint is proposed. A gradient-based nonlinear iterative algorithm is used to solve the constrained sequence design problem. Numerical results are presented to show that, compared with the state-of-the-art methods, the proposed method can produce CCS with better correlation properties and the Doppler tolerance. Finally, indoor experiments are conducted to verify the superior performance of the designed CCS, and a peak sidelobe level under −45 dB is realized on the hardware system.

Man-made targets with various orientations usually exhibit scattering diversity which makes polarimetric radar target recognition difficult. The recently developed polarimetric rotation domain techniques provide solutions to understand and utilize target scattering diversity. Meanwhile, the Null-Pol theory is the important component of target optimal polarization in radar polarimetry. This work first extends the Null-Pol theory into the polarimetric rotation domain and discloses the different scattering responses from canonical man-made structures. In this vein, the Null-Pol response pattern interpretation tool is established and a set of Null-Pol features are extracted and characterized. Then, a man-made structure identification approach is proposed based on selected features derived from the Null-Pol response pattern. Comparison studies are carried out with simulated datasets of canonical structures considering polarimetric measurement errors, simulated, and measured data of unmanned aerial vehicles (UAVs). Compared with the Cameron decomposition, the proposed method achieves more accurate and stable performance.

The use of spectral polarimetric filters in the range-Doppler domain shows great promise for clutter mitigation in weather radar applications. One limitation of these filters is that they cannot deal with situations in which ground clutter and precipitation overlap. In this letter, we propose a new signal recovery technique based on kriging in the spectral domain to recover the precipitation in clutter-contaminated areas. Using synthetic radar data, we test our new method and compare its performance to that of Gaussian model adaptive processing and bilinear interpolation. Our results indicate that kriging is the most accurate and robust technique out of the three.

The uniform and linear wind models have been commonly used for wind field retrieval in meteorological community. However, the accuracy and robustness of the retrieval results can be quite unsatisfactory due to the mismatch between these models and the real wind distribution, especially under complex wind conditions. In this article, a nonlinear model based on high-order Taylor expansion is proposed to deal with this limitation, and the combination of ridge regression and decomposition-iteration process (denoted as Ridge-DI method) is further introduced to solve the model with high accuracy and robustness. A case study on simulation and field experiment shows that the proposed method with the third-order Taylor expansion can reduce the mean root-mean-square errors (RMSEs) of the retrieved velocities by more than 16.84% in comparison with traditional methods.

Due to the orientation variation and structural complexity, designing generalized and unified features to highlight manmade target scattering from polarimetric synthetic aperture radar (PolSAR) data is challenging. Inspired by the thought of mathematical programming (MP) and coupled with the model-based decomposition, this article proposes two polarimetric features: scattering contribution combiner (SCC) and scattering contribution angle (SCA) for unified scattering characterization of manmade targets. To this end, a rotated dihedral scattering model is first constructed concerning the analogous difference reciprocal and sigmoid function transformations, which adequately reflects the transition of co- and cross-pol responses caused by the orientation variation. Along with the dipole-like compound scattering models and through designing a discriminant-based model solution method, a fine eight-component decomposition using full polarimetric information is proposed. Through skillfully employing the MP strategies, the proposed decomposition achieves the physical optimization of scattering modeling and reasonable inversion of model parameters. Thus, it can accurately describe the local structure scattering and remarkably improve the overestimation of volume scattering. Subsequently, by analyzing the significance distribution on targets of different scattering mechanisms, the SCC is constructed via the linear/nonlinear combination of scattering contributions on the one hand. On the other hand, by further mining the information implied in the scattering contributions, the SCA is proposed with the strategy of trigonometric function transformation. Experimental results conducted on real PolSAR data not only demonstrate the effectiveness and superiority of the constructed features but also exhibit a clear advantage of fine polarimetric decomposition in scattering understanding, which encourages the use of them for further applications.

The ambiguity function (AF), which is used to evaluate the range and Doppler resolutions, plays an important role in radar systems. In this article, we consider the problems of jointly designing unimodular sequence and receiving filters, and also unimodular complementary sequences and corresponding receiving filters with desired AF shapes. The design problems are formulated as the minimization of the weighted integrated sidelobe level (WISL) and the minimization of the complementary integrated sidelobe level (CISL), respectively, under the constraint of the signal-to-noise ratio (SNR) loss. Algorithms based on the alternately iterative minimization method and the majorization-minimization method are developed to tackle the optimization problems. Numerical results are demonstrated to show the superior performance of the proposed algorithms in terms of the achieved objective and running time in comparison with the state-of-the-art algorithms. Meanwhile, the excellent capability of the designed sequences to detect multiple moving targets under the strong clutter is evaluated via simulations. Moreover, the designed sequences are also implemented on an indoor hardware system, and their performance is verified.

Simultaneous polarimetric radars can measure the polarization scattering matrix (PSM) of moving targets within one pulse. The key point is the orthogonal waveform design to reduce the interference caused by the simultaneous transmission and reception. Meanwhile, to ensure the measurement accuracy of moving targets, the Doppler tolerance of the transmitted waveforms is also important. In this article, first, a matched filter (MF) at the receiver is considered and a unified framework with a newly proposed objective function to design Doppler resilient sequences under several constraints is described. The proposed objective function contains the widely used peak sidelobe level (PSL) and the integrated sidelobe level (ISL) as special cases. Meanwhile, a series of constraint conditions, including the unimodular constraint, the uncertainty modulus constraint, and the PAR constraint, is considered. Thereafter, a mismatched filter is considered for further improving the correlation properties and a similar framework for designing the optimal receiving filter at the expense of a controllable signal-to-noise ratio (SNR) loss is proposed. Numerical results are presented to verify the performance of the proposed methods. The designed sequence pair is also implemented on a fully polarimetric system to measure the PSM of a canonical target in the anechoic chamber, and the effectiveness of the proposed framework is verified by using the simultaneous polarimetric radar. It is predicted that the framework has the potential to be applied for other multichannel systems.

For current polarimetric system, the antenna usually transmits and receives electromagnetic waves with H and V polarizations which benefits the analysis and recognition of distributed targets greatly. However, for manmade target detection, the weak scattering mechanisms which characterize the structure of the target cannot be extracted with the fixed polarization. Aiming at this problem, the method proposed in this paper can be applied to suppress the strong scattering components based on target null theory. In the numerical simulation, the weak scattering mechanisms can be extracted correctly with the analysis of Cameron decomposition.

Speckle filtering of polarimetric synthetic aperture radar (PolSAR) data is a necessary preprocessing step for many subsequent applications. The performances of speckle reduction and details preservation are primarily determined by the scheme of similar pixel selection. This letter mainly contributes to establish a novel approach for adaptive and efficient selection of similar pixels. The core idea is to introduce the clustering concept to collect similar samples during the similarity test of polarimetric matrices which is functioned to be a distance measure. Adaptive clustering based on fast finding of density peaks of the data elements is adapted and an automatic determination strategy of cluster numbers is developed. Then the proposed speckle filter is established based on the distance measure and the adaptive clustering. Both unmanned aerial vehicle SAR (UAVSAR) and Radarsat-2 data sets are used for experimental studies. The demonstrations of similar pixel selection for several typical scattering patterns are carried out. The similar samples have been adaptively and precisely identified by the proposed scheme. Furthermore, the comparisons of speckle filtering performances with several advanced speckle filters clearly demonstrate the efficiency and superiority of the proposed method.

Accurate measurement of the complex permittivity of plant is essential for remote-sensing applications. The complex dielectric properties of moso bamboo (Phyllostachys heterocycla) were measured from 0.5 to 18 GHz based on the coaxial transmission/reflection method. A high-precision numerically controlled machine was used to process the bamboo samples. Based on the measured data, the complex permittivity can be better modeled as a second-order polynomial about the moisture content than the traditional exponential function. The real parts of the relative dielectric permittivity decrease with the increase in the frequency, while the imaginary parts decline first and then rise. The dielectric permittivity of the longitudinal direction is larger than that of the cross-sectional direction due to the anisotropic fibrocyte structure of moso bamboo.

Ship detection is one of important applications for synthetic aperture radar (SAR). Speckle effects usually make SAR image understanding difficult and speckle reduction becomes a necessary pre-processing step for majority SAR applications. This work examines different speckle reduction methods on SAR ship detection performances. It is found out that the influences of different speckle filters are significant which can be positive or negative. However, how to select a suitable combination of speckle filters and ship detectors is lack of theoretical basis and is also data-orientated. To overcome this limitation, a speckle-free SAR ship detection approach is proposed. A similar pixel number (SPN) indicator which can effectively identify salient target is derived, during the similar pixel selection procedure with the context covariance matrix (CCM) similarity test. The underlying principle lies in that ship and sea clutter candidates show different properties of homogeneity within a moving window and the SPN indicator can clearly reflect their differences. The sensitivity and efficiency of the SPN indicator is examined and demonstrated. Then, a speckle-free SAR ship detection approach is established based on the SPN indicator. The detection flowchart is also given. Experimental and comparison studies are carried out with three kinds of spaceborne SAR datasets in terms of different polarizations. The proposed method achieves the best SAR ship detection performances with the highest figures of merits (FoM) of 97.14%, 90.32% and 93.75% for the used Radarsat-2, GaoFen-3 and Sentinel-1 datasets, accordingly.

Speckle reduction and target detection are usually two independent and successive procedures in SAR information processing systems. The separated implementation scheme makes the determination of a suitable combination of speckle filter and target detector a challenging task in practice. This work attempts to propose a novel integrated approach for both SAR speckle reduction and target detection. Firstly, a new representation in terms of the context scattering vector and context covariance matrix is established for information augmentation and mining for SAR data. Then, similar pixels within a large moving window are selected using matrix similarity test and the similar pixel number (SPN) is recorded. The speckle reduction can be conducted with the determined similar samples and salient targets (e.g. manmade targets) can be detected with the SPN index simultaneously. Finally, the speckle reduction and ship detection integrated processing procedure is established. Experimental studies are carried out with space-borne SAR datasets. The proposed integrated framework shows superiority in both speckle reduction and target detection performances.

In order to obtain the target polarization scattering matrix (PSM), a simultaneous polarimetric measurement scheme is designed in this letter. As a complete measurement scheme, one of its hardware implementations is analyzed, and the methods of PSM estimation are proposed. Instead of employing the linear frequency modulation (LFM) waveforms with opposite slopes, the proposed scheme uses the amplitude-modulated LFM waveforms with a unitary slope. Then, the PSM estimations can be obtained from the measurements. The experimental results demonstrate that the proposed scheme has a potential advantage for the PSM measurement. When the signal-to-noise ratio is greater than 24 dB, the means of polarized correlation coefficients keep higher than 0.9. All these conclusions are verified by numerical experiments.

This article addresses the polarization scattering matrix (PSM) estimation problem of a point-like moving target. For the alternating measurement scheme, the radial displacement of the target would generate an additional phase error between two columns of the measured target PSM. Due to the decline in the performance of the traditional pulse integration (PI) method when the target is moving, the pulse compensation (PC) is discussed. Then, methods of measurement selection (MS), measurement selection with three polarizations (MS-3-Pol), and measurement selection with two nonorthogonal polarizations (MS-2-Pol) are proposed. By the estimated Doppler frequency, PC can be applied for the uniform moving target. The performance of PC degrades significantly when the target's velocity is inaccurate or unknown. However, methods of MS, MS-3-Pol, and MS-2-Pol can still be used. As the three methods do not require any a priori information about the target motion, they are suitable for situations when the target is in nonuniform motion. The MS method is sensitive to the structure of the measured PSM. Due to the three polarizations (3-Pol) scheme, MS-3-Pol is robust even for a target with small cross-polar scattering parameters. Furthermore, by the assumption of reciprocity, the 3-Pol can be simplified into a new scheme with two nonorthogonal polarization. Then, MS-2-Pol is able to estimate the moving target PSM, even if the cross-polar echoes of the target are close to zero. Compared with PI and PC, the performance of the proposed methods is irrelevant to the state of the target motion. Furthermore, when the signal-to-noise ratio is greater than 10 dB, the polarized correlation coefficients of MS-3-Pol and MS-2-Pol can be above 0.95. All the conclusions presented in this article are validated by the experimental results.

Roll-invariant polarimetric features which are independent of target orientation angle along the radar line of sight are popularly adopted in many radar application fields. During the development history of radar polarimetry, a number of roll-invariant polarimetric features have been reported in terms of different polarimetric matrix formulations, different target decomposition approaches and different scattering mechanism interpretation tools. Currently, there is lack of a comprehensive summary of these valuable roll-invariant polarimetric features. Also, their inner-relationships need to be further disclosed. Finally, deep investigations of their application potentials are essentially necessary. This work is dedicated to these aforementioned issues and a survey of roll-invariant polarimetric features is carried out.

For classical alternate measurement schemes, the motion of the target during polarization switching introduces additional phase errors in measuring the polarization scattering matrix (PSM). In this letter, we address the moving target PSM measurement problem by alternately transmitting three polarizations (3-Pol). We fully discuss the problem, including 3-Pol generation, the optimal polarization selection, and the corresponding PSM estimation, as a complete measurement approach. This measurement approach is robust to different PSMs, and its performance is not affected by the movement of the target. Compared with the classical schemes, this approach will benefit a 13-dB signal-to-noise ratio (SNR) increase for targets with small cross-polar components. Furthermore, when the SNR is greater than 15 dB, the mean of the polarized correlation coefficients is higher than 0.95. Conclusions presented in this letter are validated by the experimental results.

Sea clutter submerges the small target echo, which is disadvantageous for radar target detection. In this letter, we propose to suppress the sea clutter by orthogonal projection (OP). We construct the clutter subspace directly by the observed data vectors of neighboring range cells of the cell under test (CUT), and then suppress the sea clutter of the CUT by projecting the observed signal of the CUT to the clutter orthogonal subspace. We design a new detector which combines the cell averaging constant false alarm rate (CFAR) detector with the OP. The clutter suppression performance and computation complexity of OP are compared with those of singular value decomposition (SVD), respectively. Theoretical analysis and experimental results with real sea clutter demonstrate that the radar CFAR detection performance improves by using OP. And the CFAR detector based on OP is convenient to implement. The CFAR detection performance based on OP is the same as that based on SVD, whereas the computation complexity of OP is much less than that of SVD.

A pair of waveforms with good auto- and crosscorrelation properties is required in simultaneous polarimetric radar. Complete complementary sequence (CCS) has ideal range sidelobes along the zero Doppler axis, which is desirable in polarimetric radar. However, CCS is not widely used due to its sensitivity to the Doppler shift. In this letter, a L-BFGS (Limited Memory Broyden Flecher Goldfarb and Shanno) iterative method of constructing CCS with high Doppler tolerance is proposed, by which the range sidelobes can be suppressed in certain Doppler shifts. Numerical results are shown to demonstrate that the sidelobe peak of the designed CCS is about 30 dB lower than that of the CCS designed by the state-of-the-art GPTM (Generalized Prouhet-Thue-Morse) method in a certain Doppler shift interval.

Deep convolutional neural network (CNN) techniques have been utilized to enhance polarimetric synthetic aperture radar (PolSAR) image classification performance. This work contributes to a current challenge that is how to adapt deep CNN classifier for PolSAR classification with limited training samples while keeping good generalization performance. A polarimetric-feature-driven deep CNN classification scheme is established with both classical roll-invariant polarimetric features and hidden polarimetric features in the rotation domain to drive the proposed deep CNN model. Comparison studies validate the efficiency and superiority of the proposal. For the benchmark AIRSAR data, the proposed method achieves the state-of-the-art classification accuracies. Meanwhile, the convergence speed from the proposed CNN approach is about 2.3 times faster than the normal CNN method. For multi-temporal UAVSAR datasets, the proposed scheme achieves comparably high classification accuracies as the normal CNN method for train-used temporal data, while for train-not-used data it obtains average 4.86% higher overall accuracy than the normal CNN method. Furthermore, the proposed strategy can also produce very promising classification accuracy with very limited training samples.

In order to obtain precise measurements of the target scattering matrix, the simultaneous fully polarimetric radar imposes strict requirements on the frequency stability in terms of accurate sampling rate and intermediate frequency (IF). In this letter, the effect of frequency stability on the fully polarimetric radar with a pair of orthogonal linear frequency modulated waveforms is analyzed. Furthermore, a calibration method is proposed to calibrate the IF and the sampling rate. The calibration results demonstrate and verify the validity of the proposed method.

In synthetic aperture radar (SAR) images, scattering centers (SCs) from the same geometric structure of the man-made target usually have the same scattering type and similar coordinates. Inspired by this observation, a novel clustering-based geometrical structure retrieval (C-GSR) method is proposed to estimate the geometrical structure of targets by clustering SCs according to their types and coordinates. The C-GSR method considers each peak in a SAR image as a single SC and extracts both frequency and polarization features for classification. Then, SCs are efficiently clustered using the density-distance-based clustering algorithm. Finally, the geometrical structure corresponding to each canonical scatterer can be retrieved by computing the coordinates of SCs associated with the corresponding cluster. Experimental results have demonstrated the feasibility and accuracy of the proposed C-GSR method.

Polarimetric coherence, which has the potential to reveal physical properties of scatterers, is an important source for polarimetric SAR (PolSAR) data investigation. Target orientation relative to the PolSAR illumination direction is one key factor affecting the polarimetric coherence degree. The relative orientation between a sensor and a target can be adjusted using the rotating processing along the radar line of sight. The corresponding polarimetric coherence can be varied in the rotation domain for roll-variant scatterers. The variation of polarimetric coherence in the rotation domain contains rich hidden information which is seldom considered. This work focuses on the hidden feature exploration of polarimetric coherence in the rotation domain. A framework including a visualization tool named polarimetric coherence pattern which is able to view the polarimetric coherence properties in the rotation domain and a set of parameters to characterize the polarimetric coherence pattern has been proposed. Experimental studies validate the efficiency of the proposal.

A quick response to a large-scale natural disaster such as earthquake and tsunami is vital to mitigate further loss. Remote sensing, especially the spaceborne sensors, provides the possibility to monitor a very large scale area in a short time and with regular revisit circle. Damage ranges and damage levels of the destructed urban areas are extremely important information for rescue planning after an event. Rapid mapping of the urban damage levels with synthetic aperture radar (SAR) is still challenging. Compared with single-polarization SAR, fully polarimetric SAR (PolSAR) has a better potential to understand the urban damage from the viewpoint of scattering mechanism investigation. In radar polarimetry, the dominant double-bounce scattering mechanism in an urban area is primarily induced by the ground-wall structures and can reflect the changes of these structures. In this sense, urban damage level in terms of destroyed ground-wall structures can be indicated by the reduction of the dominant double-bounce scattering mechanism, which is the basis of this study. This work first establishes and validates the linear relationship between the urban damage level and the proposed polarimetric damage index using polarimetric model-based decomposition. Then, efforts are focused on the development of a rapid urban damage level mapping technique which mainly includes two steps of urban area extraction and polarimetric damage level estimation. The 3.11 East Japan earthquake and tsunami inducing great-scale destruction are adopted for study using L-band multitemporal spaceborne PolSAR data. Experimental studies demonstrate that the estimated damage levels are closely consistent to the ground-truth. The final urban damage level map for the full scene is generated thereafter. Results achieved in this study further validate the necessity of exploring fully polarimetric technique for damage assessment.

This paper proposes two bias correction methods for the practical planar polarimetric phased array weather radar, namely, the boresight correction and the array pattern-based correction. As an extension of the projection matrix method developed in previous research, the performance of the boresight correction considering the measurement errors of element patterns and the impacts of entire array patterns on polarimetric variables is theoretically evaluated. It is shown that the measurement errors of element patterns are crucial for the polarimetric bias correction. Furthermore, for a planar electronically scanned antenna, the measurement performance of the linear depolarization ratio varies in the beam direction, while the measurement performance of the differential reflectivity remains almost the same within the beam scan area. In order to compensate the impacts of entire array patterns on polarimetric variables, the array pattern-based correction method is formulated, and its performance is theoretically analyzed. Assessments of the analysis and future research are discussed.

Mapping of the urban damage levels with synthetic aperture radar (SAR) is still challenging. Fully polarimetric SAR (PolSAR) has the potential to identify the type of scattering mechanism changes induced by urban damage. In radar polarimetry, dominant double-bounce scattering mechanism in urban areas is primarily induced by the ground-wall structures. Thereby, within an urban patch, the reduction of the dominant double-bounce scattering mechanism reflects the urban damage level in terms of destroyed ground-wall structures, which is the basis of this study. Based on our previous study, the proposed polarimetric index is further investigated. A rapid urban damage mapping technique including mainly two steps of urban area extraction and damage level index estimation is proposed. The 3.11 East Japan Earthquake and Tsunami is adopted as the study case using multi-temporal ALOS/PALSAR PolSAR data. Experimental studies demonstrate that the estimated damage levels are closely consistent to the ground-truth.

Due to the contradiction between the high sensitivity requirement and low transmission power of weather radars with solid-state transmitters, a pulse compression technique is necessary. For the purpose of range sidelobe suppression, methods based on amplitude modulation and a mismatched filter are commonly used for target detection radars, which are not applicable for weather observations because of its drawbacks such as main lobe expansion and power loss. This letter presents a nonlinear frequency modulation pulse compression waveform to achieve a very low range sidelobe level. A mathematical model for waveform design is established, in which the time-frequency relation is expressed as the combination of a linear function and a sine series. Thus, a set of parameters can fully characterize the time-frequency curve. By using a simulated annealing algorithm, the optimal parameter set can be obtained, which shows that a peak sidelobe level under -60 dB is achievable. Finally, this kind of waveform is implemented on hardware, and its performance is verified.

This paper focuses on earthquake/tsunami damage investigation over urban areas by exploring the multitemporal spaceborne ALOS/PALSAR PolSAR data. The polarimetric scattering mechanism changes before- and after-tsunami, at the city block scale, have been examined using model-based decomposition and PO angle techniques. These analyzes are used to establish the relationships between the polarimetric scattering mechanism changes and damage levels. The basic scattering structures such as ground-wall dihedral structures from the built-up areas were found to be stable even over a long temporal baseline. Two polarimetric indexes have been proposed for damage level indication. Experimental results validate the efficiency of these two indicators, since the built-up areas with different damage levels can be well discriminated. These results demonstrate the importance and efficiency of full polarimetric information for natural disaster assessment.

The overestimation of volume scattering power and the scattering mechanism ambiguity are still present in model-based decompositions even with the implementation of the deorientation processing. These effects are demonstrated and investigated. One possible reason is because of the limited dynamic range of the models themselves that are not fully satisfied for the mixed scene cases. An empirical volume scattering model is proposed, using the repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) coherence, to extend the model dynamic range to be more adaptive. PolInSAR coherence is sensitive to different types of forests and terrains. The proposed model inherits these characteristics. In addition, it considers the cross-polarization power induced by oriented man-made structures. Thereby, a model-based polarimetric decomposition scheme is developed. The efficiency of the proposed method is demonstrated using E-SAR airborne and ALOS/PALSAR spaceborne repeat-pass PolInSAR datasets. Comparative experiments are carried out and show that the proposed decomposition overcomes the scattering mechanism ambiguity between forests and oriented built-up areas, since it successfully identifies the oriented buildings as double- or odd-bounce man-made structures while keeping the volume scattering dominant for the forests. Besides, the stable decomposition performance over the oriented built-up patches with quite different orientation angles also validates the improvement of the proposed decomposition. In addition, the demonstrations with short and long temporal baselines validate the generality of the proposed method.

This paper presents the development of a uniform polarimetric matrix rotation theory in the rotation domain along the radar line of sight for polarimetric synthetic aperture radar (PolSAR) data interpretation. The uniform representation of each coherency matrix element is a sinusoidal function in the rotation domain. A set of oscillation parameters, including oscillation amplitude, oscillation center, angular frequency, and initial angle, is proposed to fully characterize the scattering behavior in the rotation domain. A set of rotation angle parameters, including stationary angle, null angle, and minimization/maximization angles, is derived to indicate specific states of the rotation property. The rotation relationships between the coherency and covariance matrices with linear and circular polarization bases are established. A look-up table for these parameters is provided, and their physical meanings are interpreted. These derived parameters directly link to the Huynen parameters. Therefore, the proposed theory has the ability to achieve a desired state of one Huynen parameter by rotating the polarimetric matrix at a designated rotation angle. This theory also generalizes both the classic polarization orientation angle originally derived from the covariance matrix in a circular polarization basis and the deorientation theory developed from the minimization of the cross-polarization term. The roll-invariant terms have also been summarized. Finally, multifrequency Pi-SAR and AIRSAR PolSAR data sets are used to demonstrate the derived parameters. One oscillation amplitude parameter has been verified to be especially suitable for characterization of oriented man-made targets. Two angle parameters are sensitive to the reflection symmetry condition and crop types. Therefore, a simple unsupervised classification scheme has been developed and demonstrated. Further utilization perspectives of the proposed theory have been discussed.

Orientation angle compensation was incorporated into model-based decomposition to cure overestimation of the volume scattering contribution for interpretation of polarimetric synthetic aperture radar (PolSAR) data. The compensation is based on rotating the coherency matrix to minimize the cross-polarization term. However, this processing cannot always guarantee that the double- and odd-bounce scattering components will be rotated back to zero orientation angle and left with zero cross-polarization power. As a result, built-up patches with large orientation angles may still suffer from the scattering mechanism ambiguity. In this paper, double- and odd-bounce scattering models were generalized to fit the cross-polarization and off-diagonal terms, by separating their independent orientation angles. A general decomposition framework is proposed that utilizes all elements of a coherency matrix. The residual minimization criterion is used for model inversion. All the model parameters are simultaneously obtained using a nonlinear least squares optimization technique. The manual intervention, branch conditions, and negative power issues are avoided. The performance and advantages of this approach are demonstrated and evaluated with spaceborne L-band ALOS/PALSAR and airborne X-band Pi-SAR PolSAR data sets. Comparison studies are also carried out and demonstrate that further improved decomposition performance is achieved by the proposed method, especially in oriented built-up areas.

This paper presents the development of a uniform polarimetric matrix rotation theory in the rotation domain along the radar line of sight for polarimetric SAR (PolSAR) data interpretation. The uniform representation of each coherency matrix element is a sinusoidal function in the rotation domain. A set of oscillation parameters, including oscillation amplitude, oscillation center, angular frequency and initial angle, is proposed to fully characterize the scattering behavior in the rotation domain. A set of rotation angle parameters, including stationary angle, null angle, and minimization/maximization angles, is derived from the angular frequency and initial angle to indicate the specific states of the rotation property. A look-up table for these parameters is provided and their physical meanings are interpreted. The proposed theory generalizes both the classic polarization orientation (PO) angle originally derived from the covariance matrix in a circular polarization basis and the deorientation theory developed from the minimization of the cross-polarization term. The roll-invariant terms have also been summarized. Finally, multi-frequency AIRSAR and Pi-SAR PolSAR data sets are used to demonstrate the derived parameters.

The growing interest in 3-D reconstruction of targets, particularly man-made objects, has made synthetic aperture radar (SAR) tomography a hot topic in recent years. It obtains a 3-D reflectivity map by coherently processing multiple images acquired from slightly different views. This paper investigates the use of polarimetric tomographic SAR to reconstruct 3-D images of man-made objects and proposes a polarimetric 3-D reconstruction technique, based on the multiple-measurement vector compressive sensing (CS) (MMV-CS) model and Tikhonov regularization theory. The main feature of the technique is that of allowing joint reconstruction of polarimetric 3-D reflectivity maps with high resolution. For X-band tomographic SAR, we demonstrate that the phase error induced by an array element error is severe enough to prevent data focusing and propose a phase calibration technique employing prominent scatterers to adapt the proposed technique to practice. To check the plausibility of our algorithms, a ground-based SAR system is introduced, and high-resolution 3-D images obtained by processing the real collected data are presented. As special cases of the new proposed technique, both the Tikhonov regularization and the MMV-CS method reconstruct the targets successfully and give an accurate estimate for the vehicle size. Compared to the Tikhonov regularization method, the MMV-CS technique exhibits much better superresolution power and lower sidelobe level. The advantage of the MMV-CS technique over the single-measurement vector CS technique is also demonstrated, and the phase calibration algorithm is verified.

In the area of speckle filtering, proper averaging of samples with similar scattering characteristics is of great importance. However, existing filtering algorithms are either lack of similarity judgment of scattering characteristics or using only intensity information for similarity judgment. In this paper, a novel polarimetric SAR (PolSAR) speckle filtering algorithm based on mean shift theory is proposed. By using range-spatial joint mean shift theory in Riemannian manifold, the pixels chosen for averaging are ensured to be close not only in scattering characteristics but also in spatial domain. Experiment results show that the proposed speckle filtering algorithm achieves good performance in terms of speckle filtering, edge protection as well as polarimetric characteristics preservation.

A new polarimetric tomography technique based on compressive sensing is proposed in this paper for the applications such as 3D reconstruction of man made target. Compared to the existing methods, the advantages of this new technique are those of preserving full image resolution, no model order selection procedure, high resolution, and low sidelobe artifacts. The effectiveness of the technique is demonstrated by processing real data collected by ground rail SAR.

Most polarimetric synthetic aperture radar interferometry (PolInSAR) data processing procedures and their applications are based on the polarimetric complex coherence descriptor. The reliable estimation of the complex coherence requires selecting sufficient homogeneous pixels for generating an unbiased estimator. In this paper, two indicators using only polarimetric and both polarimetric and interferometric information are derived as the similarity measures for complex Wishart distributed PolInSAR covariance matrix, respectively. Using these indicators, a double similarity test scheme, which shows high sensitivity to both polarimetric and interferometric properties, is proposed for similar pixel selection. The full information utilization could characterize the homogeneous pixels more accurately. Furthermore, since the similarity test has the potential to reject the pixels with different populations, it is suitable to be applied in a large searching area (e.g., 15 × 15 window) to accept sufficient homogeneous pixels. Thereby, combining with unbiased estimator, reliable estimation is achieved. The efficiency and advantage of the proposed estimation scheme are demonstrated with the aid of simulated and real PolInSAR data sets.

This paper is comment on “Orientation Angle Preserving A Posteriori Polarimetric SAR Calibration”.

An extraction method of the polarimetric atmospheric target has been proposed to obtain most useful information with noise, clutter and artificial signals as less as possible for dual- orthogonal frequency modulation continuous wave (FMCW) polarimetric radar. The signal processing is described for dual- orthogonal FMCW polarimetric radar. The polarimetric range- Doppler spectra of precipitation obtained in a single sweep time are calibrated by radar constant calibration and reciprocity modification. The mask matrix for filtering is constructed based on the double spectral linear depolarization ratios (sLdr) and mathematical morphology methods. The precipitation atmospheric targets are extracted successfully by multiplying the mask matrix with the measured range-Doppler spectra by the polarimetric agile radar SAnd X-band (PARSAX) radar. The proposed technique keeps more atmospheric targets and suppresses more clutter, noise and artificial signals compared with the original data and the data after double sLdr filtering combined with noise clipping.

In this study, we consider tree vertical profile with a higher order truncation of Fourier-Legendre series using polarization coherence tomography. An improved method based on Freeman-Durben decomposition is employed to estimate tree height and surface phase. A contrast to single-baseline scenario is performed. The primary scattering mechanisms and polarization dependence are interpreted by vertical profile reconstructions. Results are validated using simulation data