During the last decade, synthetic aperture radar (SAR) tomography (TomoSAR) technique in 3D reconstruction is significantly improved. In particular, compressed sensing (CS) has become the best suit for urban tomographic inversion. Among CS algorithms, the orthogonal matching pursuit (OMP) combined with Bayesian information criterion (BIC) has relatively low computational complexity, however, its scatterer estimation accuracy needs to be improved. To address the problem, a prior scatterer estimation with an innovative triplethreshold detection algorithm is proposed which not only greatly reduces number of iterations but also helps suppress artifacts. Experiments on real data show that the priori overlay times maps provided by the proposed algorithm are closer to the reference maps than other two pre-estimation algorithms. Artifacts in 3D reconstruction results are well suppressed at less than half the time cost of original OMP-BIC.

In this article, an effective clutter suppression algorithm is presented for the space-borne azimuth multiantenna high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system, which is based on the null-space technique. First, the echo of bistatic geosynchronous-low earth orbit (GEO-LEO) azimuth multiantenna HRWS SAR-ground moving target indication (GMTI) system is utilized to deduce the coarse-focused image of moving targets and clutter, where the Chirp Fourier transform (CFT) in azimuth is involved. Then, the matrix form can be utilized to describe the coarse-focused image of the multiantenna SAR system and the corresponding covariance matrix can be estimated. After that, the null-space is constructed using the covariance matrix corresponding to clutter, where at least a redundant channel freedom is required. Since the null-space vector is orthogonal to signal-space vector, it can be used to suppress the clutter. As an equivalent phase is brought by the slant velocity, the moving targets’ echo can be preserved during clutter suppression. Then, the optimization and suboptimization vectors for clutter suppression are introduced. It is worth noting that the proposed clutter suppression algorithm is robust for the antenna mismatch, that is, the antenna mismatch in phase and the corresponding position error. Finally, the theoretical investigations are validated using some simulation experiments, where the experiments for bistatic GEO-LEO and single-platform azimuth multiantenna HRWS SAR-GMTI system are both included. In addition, the real measured single-platform azimuth multiantenna HRWS SAR data experiments are also performed.

With the great development of synthetic aperture radar (SAR) technique, more accurate and efficient coregistration is needed for high resolution interferometric SAR (InSAR) data before phase filtering and unwrapping. To improve the time efficiency and the coregistration accuracy for meter/dimeter-level resolution data, this paper proposes an adaptive subpixel coregistration method, which brings the adaptive window for the maximum spectrum peak algorithm (MSP A). Experiments are performed on both stripmap data and spotlight data to validate the effectiveness of the proposed method.

This paper proposes a new scheme of motion parameter estimation and relocation for airborne three-channel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. Compared with the conventional straight-path SAR, the parameter estimation of a target is more challenging because the target's range history and signal model are more complicated due to the complexity of the relative motion between CSSAR and ground moving target. In this paper, the signal model of a ground moving target and the expression for its along-track interferometric (ATI) phase from the environment of airborne three-channel CSSAR are derived. The coupling effect among the target's motion and position parameters is also figured out. Then, a scheme of motion parameter estimation and relocation is proposed. The proposed scheme utilizes the ATI phase and the quadratic-term coefficient in the range equation to estimate the target's motion and position parameters and utilizes an iterative strategy to address the coupling effect among these parameters. Numerical simulations are conducted to validate the satisfactory performance achieved by the proposed algorithm.

In this paper, the physical optics method is employed to study the problem of characteristics analysis and image processing for full-polarization synthetic aperture radar (SAR), where electromagnetic scattering from a flat horizontal perfect electric conducting (PEC) reflector is involved. The model of the full-polarization SAR echo from a small region of flat horizontal PEC reflector is deduced based on the dyadic Green's function theory. With the available echo model, image processing and results are presented for the full-polarization SAR. For the horizontal co-polarization channel, the amplitude of imaging result descends with the squint angle, where the well-focused imaging result can always be obtained. On the contrary, the amplitude of cross-polarization channel imaging results is increased with the squint angle. When the radar works in the side-looking mode or low-squint mode, the cross-polarization channel echo cannot be well focused. For the high-squint mode, it can be well focused. For the horizontal co-polarization channel, the amplitude of well-focused result can be approximately regarded as a constant for all squint angles. The effectiveness of the characteristics analysis results is demonstrated via simulated and real measured Ka-band airborne full-polarization SAR data.

Similar to the conventional squint mode synthetic aperture radar (SAR) imaging processing, the estimation of Doppler centroid is one key problem for the low-squint-mode (within the range of [-5°, 5°]) multichannel in an azimuth high-resolution and wide-swath (HRWS) SAR system. In this paper, based on the electromagnetic scattering model, a novel weighted Doppler centroid estimation approach is proposed for the multichannel in the azimuth HRWS (MC-HRWS) SAR system. First, Maxwell's equations are employed to derive the echo model for the multichannel SAR system. Then, an improved backscattering model is presented based on the small perturbation method and the available echo model, which is adopted to produce the weights for Doppler centroid estimation. More importantly, in order to improve the precision of Doppler centroid estimation, a weighted ambiguity-free Doppler centroid estimation approach is proposed, where the range-variant characteristic of Doppler centroid is employed to resolve the ambiguity number of Doppler centroid, and the echoes from different range bins with different signal-to-noise ratios are considered. In addition, the Cramer-Rao low bound of the estimated Doppler centroid is also discussed in this paper. The effectiveness of the proposed Doppler centroid estimation approach is verified via simulated and real measured low-squint-mode MC-HRWS SAR data.

In this letter, a novel estimation approach for the Doppler chirp rate and baseline in azimuth is proposed for the multichannel in azimuth high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system. First, a range-invariant Doppler chirp rate estimation approach is developed based on a map drift algorithm and correlation function method. Then, a weighted local maximum-likelihood approach is adopted to obtain an accurate estimation of the range-variant Doppler chirp rate. With an accurate Doppler chirp rate, the baseline in azimuth can be estimated, which is developed from the correlation function between the echoes of adjective channels. The proposed approaches are successfully applied to process real five-channel HRWS SAR echo data, demonstrating the efficacy of the proposed methods.

This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches.

For high-resolution wide-swath (HRWS) SAR based on multiple receive apertures in azimuth, this paper proposes a novel imaging approach for moving targets. This approach utilizes the wide bandwidth characteristics of the transmitted signal (multiple wavelengths) to estimate the moving target velocity. First, this paper explains that there is a phase mismatch (PM) between azimuth channels for the echo of a moving target, which depends on range frequency. In order to correct the PM, an algorithm based on local maximum-likelihood minimum entropy is proposed. The linear dependence of the PM on range frequency is employed to estimate the target velocity. Second, after the signal reconstruction in Doppler frequency and the compensation of the PM for a moving target, the estimated target velocity is utilized to implement the linear range cell migration correction and the Doppler centroid shifting. Then, the quadratic range cell migration is corrected by the keystone processing. After that, the focused moving target image can be obtained using the existing azimuth focusing approaches. Theoretical analysis shows that no interpolation is needed. The effectiveness of the imaging algorithm for moving targets is demonstrated via simulated and real measured ship HRWS ScanSAR data.

In order to obtain high-resolution wide-swath (HRWS) images, the multichannel in azimuth synthetic aperture radar (SAR) system has been adopted to deal with the contradiction problem between high resolution and low pulse repetition frequency (PRF). In this paper, a novel channel-calibration method is proposed for the multichannel in azimuth HRWS SAR imaging system. During the channel calibration, the mismatch between the channels, which results from the gain-phase error and the range sampling time error, is first corrected by the coarse-calibration processing in the range frequency domain. Then, the along azimuth baseline measurement error is estimated. Considering the range variance in the residual phase error, the data are processed in blocks along the range time domain, and the error of every subblock data is estimated. After that, a fitting and filtering is implemented along the range to the estimated values of the phase error of all subblocks. The range-variant phase error is then compensated using their estimated values. After channel calibration, this paper also presents a new Doppler ambiguity suppression algorithm which nulls the ambiguity components in the Doppler domain. The newly proposed algorithm outperforms the post-Doppler ambiguity suppression algorithm. The airborne real measured scan synthetic aperture radar data, which are acquired by a seven-channel in azimuth SAR imaging system with the system working at X-band, are utilized to demonstrate the performance of the newly proposed channel-calibration method and the new Doppler ambiguity suppression algorithm.

In this letter, we discuss the problem that linear range cell walk correction in the azimuth time domain may cause space variation along the azimuth not only to the quadratic phase but also to the quadratic range cell migration (QRCM) under the conditions of high resolution and large scene along the azimuth. Moreover, an algorithm is proposed to deal with this problem. The proposed algorithm adopts the azimuth space variation filtering in the range frequency domain. In addition, the range-dependence component of QRCM is corrected by linear chirp scaling, and the unified QRCM can be corrected in the 2-D frequency domain. The proposed algorithm, without interpolation, can be easily implemented by integrating with motion compensation for image processing. Simulation and airborne strip-map real data show the accuracy and efficiency of the proposed algorithm.

High-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is an essential tool for modern remote sensing. To effectively deal with the contradiction problem between high-resolution and low pulse repetition frequency and obtain an HRWS SAR image, a multi-channel in azimuth SAR system has been adopted in the literature. However, the performance of the Doppler ambiguity suppression via digital beam forming processing suffers the losses from the channel mismatch. In this paper, a robust channel-calibration algorithm based on weighted minimum entropy is proposed for the multi-channel in azimuth HRWS SAR imaging. The proposed algorithm is implemented by a two-step process. 1) The timing uncertainty in each channel and most of the range-invariant channel mismatches in amplitude and phase have been corrected in the pre-processing of the coarse-compensation. 2) After the pre-processing, there is only residual range-dependent channel mismatch in phase. Then, the retrieval of the range-dependent channel mismatch in phase is achieved by a local maximum-likelihood weighted minimum entropy algorithm. The simulated multi-channel in azimuth HRWS SAR data experiment is adopted to evaluate the performance of the proposed algorithm. Then, some real measured airborne multi-channel in azimuth HRWS Scan-SAR data is used to demonstrate the effectiveness of the proposed approach.

The goal of this paper is to suppress the narrowband interference (NBI) and wideband interference (WBI) in synthetic aperture radar (SAR) by using a nonparametric method. The method is based on the analysis of time-frequency characteristic of NBI and WBI from which an interference suppression filter combined with the constant false alarm rate algorithm is designed. In this approach, the short-time Fourier transform (STFT) is used to estimate the instantaneous frequency of the SAR echo data with interference. In the STFT domain, the instantaneous frequency spectrum is represented by wavelet, and then, the designed filter filters the corresponding wavelet coefficients of the interference components. In addition, this algorithm is robust to time-varying NBI and WBI. The performance of the proposed approach is evaluated by the simulated and measured data, and the effectiveness is demonstrated.