The increasing complexity of the electromagnetic environment poses significant challenges to jamming countermeasures. Active jamming recognition serves as a crucial prerequisite for active jamming countermeasures. Addressing the blindness of feature extraction in radar active jamming recognition, this paper proposes an active jamming recognition method based on Fisher discriminant and feature selection. This method employs the Fisher discriminant criterion to theoretically derive feature separability and rank the importance of feature attributes. the features with the best performance are selected as inputs for the classifier. The proposed method substantially reduces the computational cost of feature extraction without compromising recognition accuracy. In simulation experiments, when jamming-to-noise ratio is above$-$5 dB, the recognition rate consistently exceeds 96%, demonstrating superior generalization and robustness.

Rotating phased array radars (RPARs) utilize advanced technology for meteorological observations; however, these radars may experience misalignment in azimuth pointing. This study proposes a calibration approach for azimuth pointing in RPARs based on ground clutter (GC) correlation. First, the proposed method adaptively determines the number of clutter bins for each direction in the plan position indicator. Second, the azimuth calibration numbers are derived by optimizing the correlation between the GC echoes of two successive scans. Third, in light of the radar’s physical rotation constraints, the proposed method includes a process for handling situations when GC is not available. The effectiveness of the proposed method was experimentally assessed using data from thousands of rays collected under both rainy and clear-air conditions. The results obtained using the proposed method demonstrate an improvement compared with radar readings using standard angle encoders. This azimuth pointing calibration method is easy to carry out and achieves more accurate azimuth angles than current methods; it has the potential for use in operational radars.

In the context of escalating frequency spectrum congestion, the prevalence of radio frequency interference (RFI) poses a growing challenge for weather radars, compromising data quality and adversely affecting the accuracy of variable estimations. This article proposes a novel algorithm for the separation of precipitation and RFI, based on low-rank sparse decomposition (LRSD). When precipitation and RFI overlap, this method effectively filters out RFI while minimizing its impact on precipitation by analyzing the property difference between precipitation and RFI in the time domain. The proposed algorithm operates on the assumption that precipitation exhibits low-rank properties, whereas RFI manifests as sparse signals. This assumption is grounded in the observation that RFI in weather radars is typically unintentional, occupying a limited number of pixels in the range-time power image, while precipitation demonstrates approximate stationarity with a slow speed within a coherent processing interval (CPI). This algorithm is intended to alleviate the adverse effects of RFI, and the efficacy of the approach is validated using data collected by polarimetric Doppler weather radar systems at the Royal Netherlands Meteorological Institute. This article systematically evaluates the impact of the proposed LRSD method in comparison to two traditional RFI mitigation strategies (e.g., the Vaisala-3 method and 2-D filter) on the quality of meteorological data. The results demonstrate that the proposed LRSD method outperforms the alternatives in terms of RFI suppression and precipitation retention performance. At present, the LRSD method loses phase information, which may impact the accuracy of measuring polarization parameters of precipitation.

One of the significant challenges in using polarimetric phased array radars (PPARs) for weather observations is the implementation of dual polarization with an acceptable level of cross-polar isolation induced by the antenna. This article quantitatively analyses and compares the bias caused by cross-coupling in different modes. For the alternately transmitting and simultaneously receiving (ATSR) mode, simultaneously transmitting and simultaneously receiving (STSR) mode, and the pulse-to-pulse phase coding STSR (PC-STSR) mode, the bias is quantified as a function of the maximum cross-polar power, while for the alternate orthogonal waveform STSR (A-OW-STSR) mode, the bias is a function of the maximum cross-polar power and waveform isolation. In the meantime, the cross-polar isolation required in different modes to attain the accuracy of polarization and spectral moment parameters measurement is quantitatively analyzed. The results from theoretical developments and simulation analysis exhibit that the A-OW-STSR mode can obtain an unbiased estimate of velocity and have an equal requirement for cross-polar isolation as the PC-STSR mode. In addition, the A-OW-STSR mode can not only obtain the polarization scattering matrix (PSM) of the target within one pulse repetition time but also ensure accurate precipitation observation. Therefore, it can be used as an alternative transmitting mode for multifunction PPAR.

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.

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.

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.

Compact polarimetry synthetic aperture radar (compact-pol SAR) provides relatively rich polarimetric information while maintaining a wide swath, which is quite suitable for the earth observation. Urban area is important observation of remote sensing. However, the backscattering of manmade targets, including urban areas, is sensitive to the relative geometry between target orientation and the radar line of sight, which still makes urban area extraction a challenge. Polarimetric correlation pattern is a tool to mine target hidden information within scattering diversity. This study extends the polarimetric correlation pattern to compact-pol SAR for urban area extraction, which mainly contains three steps. Firstly, pseudo quad polarimetry (qual-pol) data is generated from compact-pol SAR data based on Nord's method. Then, polarimetric correlation pattern features are extended to pseudo quad-pol data. Finally, the urban area is extracted using the superpixel CFAR detection method. Experimental studies are carried out with airborne PiSAR and spaceborne ALOS-2 datasets. Compared with traditional compact-pol features, the proposed extended polarimetric correlation pattern features achieve superior performances.

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 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.

The scattering mechanism interpretation of oriented manmade targets especially those with large orientation angles is a challenging task. Recently, to fit the cross-polarization and off-diagonal terms, physically meaningful double-bounce and odd-bounce scattering models have been developed by modeling their independent orientation angles. Nevertheless, parameters inversion of these models is a nonlinear optimization procedure. The main purpose of this work is to convert the nonlinear model inversion procedure to a linear solution while inheriting the generalized models. By disclosing the latent relationship between the polarization orientation angle and double-bounce orientation angle, a double-bounce orientation angle inversion method is developed. Then a refined double-bounce scattering model is proposed and a fast general model-based decomposition is established. The comparison experiments are performed on PiSAR data. Compared with the state of art approaches, the proposed decomposition method achieved improved decomposition performance from both visual and quantitative investigation for oriented built-up areas.

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.

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.

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.

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.

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.

Feature extraction and recognition of wobbling targets are very important in spatial target surveillance. It has been shown that the scattering centers are slipping on the edge of the rotational symmetry target with the target micro-motion according to the electromagnetic scattering theory and electromagnetic computation analysis. Based on the slippery scattering center model, the micro-motion model and high-range resolution profile (HRRP) model of a wobbling rotational symmetry cone-shaped target are introduced, and the observed HRRP sequence is used to construct a time-range distribution matrix, then a estimation method of the wobbling period is proposed based on time-range distribution matrix correlation, which is validated by electromagnetic computation data and dynamic simulation.

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.

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.

As having the imaging ability of area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, the currently exploited imaging algorithms of forward-looking SAR suffer from poor azimuth resolution induced by limited azimuth aperture length. To address this challenge, we develop a super-resolving imaging algorithm for forward-looking SAR based on compressive sensing theory. Firstly, the spatial geometry and signal model of forward-looking SAR is analyzed. After that, the compressive sensing theory is introduced to improve azimuth resolution. Imaging simulations based on Ku-band image data from the MiniSAR system demonstrate the effectiveness of the proposed method.

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 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 2-D image of a spinning target obtained by monostatic radar is modified by the angle between the spinning axis and the radar line of sight, so it usually cannot describe the real size of the target. The T/R-R bistatic radar is proposed to solve this problem. First, the bistatic geometry and bistatic echo signals of a spinning target are modeled. Then, a novel 2-D imaging algorithm is presented based on the connections between the mono- and bistatic echoes of the same scatterer and the classical Hough transform, allowing both the mono- and bistatic 2-D images of the spinning target to be obtained simultaneously. The theoretical analysis is carried out by the electromagnetic calculation and numerical simulations.

A new cross-channel interference suppression method based on the fractional Fourier transform (FRFT) is proposed to eliminate the effect due to cross-channel interference when a full-polarimetric radar adopts the opposite-slope linear frequency modulation transmit signals and de-ramping processing in the simultaneous measurement mode. The FRFT with an appropriate order is operated on the signals in the cross-interference interval. Such order is obtained via the calculation of the frequency-modulation slope of transmitted signals. The cross-channel interference is changed into sinc functions that are detected by a designed threshold and filtered out in the FRFT domain to suppress the cross-channel interference. The simulations show that the proposed method can obviously reduce the peak sidelobe levels and the integrated sidelobe levels of targets in range profiles compared with the traditional method, which is benefit to improve the detection and measurement performances of weak polarimetric scattering components. The proposed method is suitable for stable or slow-moving targets.

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.

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.