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Ground-Based Synthetic Aperture Radar (GB-SAR), due to its high precision, high resolution, and real-time capabilities, is widely used in the detection of slope deformations. However, the weak scattering coefficient in low-coherence areas poses a great challenge to the observation point selection accuracy. This paper introduces a selection process for reliable observation points that integrates phase and spatial information. First, for various observation points with differentiated stability, we propose to utilize maximum likelihood estimation (MLE) methods to achieve stability assessment. Second, a phase correction approach is proposed to address unwrapped phase errors encountered at less stable points. Third, adaptive filtering for deformation information at observation points is achieved using estimated variance combined with wavelet filtering thresholds. Finally, in dealing with unknown deformation trends, we propose utilizing a clustering method to accurately identify these trends, thereby enhancing the precision in identifying reliable observation points (ROPs). The experimental results demonstrate that this method enhances the accuracy of observation point selection in low-coherence areas, providing a broader observational field for deformation detection. [ABSTRACT FROM AUTHOR]

A trend in the development of spaceborne Synthetic Aperture Radar (SAR) technology is the shift from a single-satellite repeated observation mode to a multi-satellite collaborative observation mode. However, current multi-satellite collaborative geolocation algorithms face challenges, such as geometric model mismatch and poor baseline estimation accuracy, arising from highly dynamic changes among multi-satellites. This paper introduces a high-precision and efficient geolocation algorithm for a spaceborne bistatic interferometric SAR (BiInSAR) system based on an improved range–Doppler (IRD) model. The proposed algorithm encompasses three key contributions. Firstly, a comprehensive description of the spatial baseline geometric model unique to the bistatic configuration is provided, with a specific focus on deriving the perpendicular baseline expression. Secondly, IRD geolocation functions are established to meet the specific requirements of the bistatic configuration. Then, a novel BiInSAR geolocation algorithm based on the IRD's functions is proposed, which can significantly improve the target geolocation accuracy by modifying the range–Doppler equation to suit the bistatic configuration. Meanwhile, a low-coupling parallel calculation method is proposed, which can improve the calculation speed by two to three times. Finally, the accuracy and efficiency of the algorithm are demonstrated using experimental data acquired by the TH-2 satellite, which is China's first spaceborne BiInSAR system. The experimental results prove that the IRD algorithm exhibits geolocation accuracy with an average error of less than 1 m and a standard deviation of less than 2.5 m while maintaining computational efficiency at a calculation speed of 1,429,678 pixels per second. [ABSTRACT FROM AUTHOR]

Polarimetric Synthetic Aperture Radar (PolSAR) data is inherently characterized by speckle noise, which significantly deteriorates certain aspects of the quality of the PolSAR data processing, including the polarimetric decomposition and target interpretation. With the rapid increase in PolSAR resolution, SAR images in complex natural and artificial scenes exhibit non-homogeneous characteristics, which creates an urgent demand for high-resolution PolSAR filters. To address these issues, a new adaptive PolSAR filter based on joint similarity measure criterion (JSMC) is proposed in this paper. Firstly, a scale-adaptive filtering window is established in order to preserve the texture structure based on a multi-directional ratio edge detector. Secondly, the JSMC is proposed in order to accurately select homogeneous pixels; it describes pixel similarity based on both space distance and polarimetric distance. Thirdly, the homogeneous pixels are filtered based on statistical averaging. Finally, the airborne and spaceborne real data experiment results validate the effectiveness of our proposed method. Compared with other filters, the filter proposed in this paper provides a better outcome for PolSAR data in speckle suppression, edge texture, and the preservation of polarimetric properties. [ABSTRACT FROM AUTHOR]

Multichannel parameter estimation is a key technology for azimuth multichannel terrain observation by progressive scans synthetic aperture radar (MC TOPS SAR) systems. Normally, for the traditional multichannel parameter estimation algorithms, the mismatch parameters are concluded as phase error, baseline error, and Doppler centroid. The beam rotation speed error is ignored. However, for MC TOPS SAR, beam rotation speed error will degrade the reconstruction performance of the Doppler spectrum. Moreover, only part of the mismatch parameters can be estimated for the traditional algorithms. To address those problems, a joint parameters estimation algorithm for TOPS SAR based on spatial time cross correlation coefficient (STCCC) is proposed. Combined with phase wrapping and the least-squares method (LSM), the algorithm is capable of realizing a joint parameters estimation of channel consistency error, azimuth baseline error, Doppler centroid frequency, and beam rotation speed estimation without iteration. The real data processing result shows that the method can effectively realize MC TOPS SAR data error estimation. [ABSTRACT FROM AUTHOR]

Ground-based synthetic aperture radar (GB-SAR) is a highly effective technique that is widely used in landslide and bridge deformation monitoring. GB-SAR based on multiple input multiple output (MIMO) technology can achieve high accuracy and real-time detection performance. In this paper, a novel method is proposed to design transmitting and receiving array elements, which increases the minimum spacing of the antenna by sacrificing several equivalent phase centers. In MIMO arrays, the minimum antenna spacing in the azimuth direction is doubled, which increases the variety of antenna options for this design. To improve the accuracy of the system, a new method is proposed to estimate channel phase errors, amplitude errors, and position errors. The position error is decomposed into three directions with one compensated by the phase error and two estimated by the strong point. Finally, we validate the accuracy of the system and our error estimation method through simulations and experiments. The results prove that the GB-SAR system performs well in bridge deformation and vibration monitoring with the proposed method. [ABSTRACT FROM AUTHOR]

In forward‐looking imaging, left‐right Doppler is ambiguous and cross‐range resolution is limited by real aperture, which result in traditional synthetic aperture radar imaging methods no longer applicable. Besides, the impact of three‐dimensional acceleration on an over‐complete dictionary matrix and sparse reconstruction kernel is not considered in conventional super‐resolution forward‐looking imaging methods. To solve these problems, a super‐resolution forward‐looking imaging method for manoeuvering platforms is proposed. First, the range walk caused by forward‐looking geometry and higher‐order phase introduced by three‐dimensional acceleration are eliminated by compensating a pre‐processing function. Subsequently, according to beam steering‐based geometry and linear regression model, the over‐complete dictionary matrix is optimised to more accurately describe the complicated forward‐looking geometry with curved trajectory. Finally, sparsity adaptive matching pursuit kernel with an improved halting condition is adopted to reconstruct the forward‐looking scene. The proposed method is supported by point target simulation and surface target simulation. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) sometimes needs to be imaged with small time bandwidth product (TBP) for fast observation. As a real-time image algorithm, back-projection algorithm (BPA) is efficient for fast observation. However, compared with the frequency-domain algorithm, the influence of small TBP (STBP) on BPA has not been fully discussed. Thus, the performance of the original BPA on STBP SAR imaging is analyzed and an improved BPA for STBP imaging is proposed in this letter. Theoretical analysis indicates that STBP will cause the point spread function (PSF) distortion and azimuth spectrum ambiguity to the BPA imaging result. To deal with those problems, two parameters of the original BPA are modified in the improved BPA. The accumulating azimuth angle (AAA) is optimized first to calibrate the PSF distortion. Then, based on the azimuth-ambiguity-to-signal ratio (AASR), a BPA meshing criterion related to TBP is proposed to diminish azimuth spectrum ambiguity. The simulation and real data results demonstrate that the improved BPA is effective on undistorted PSF recovering and unambiguity spectrum maintaining, even when the TBP is down to 4. [ABSTRACT FROM AUTHOR]

Spaceborne bistatic multichannel synthetic aperture radar (MC-SAR) system employed inclined geosynchronous Earth orbit (GEO) transmitter and low-Earth-orbit (LEO) receiver can provide fine spatial resolution and a vast area of surveillance, which presents great potentials for future Earth observation. Nevertheless, owing to special geometry and big differences of orbital characteristics, the conventional effective phase centre (EPC) operation for unambiguous SAR signal reconstruction cannot be directly used. To address the issue, starting from geometry model of GEO-LEO bistatic MC-SAR, the new effective positions of the receiving channels are obtained. Then, the time-variant characteristics of residual phase error after the presented EPC processing is analysed. Finally, the method of reconstructing unambiguous SAR signal is presented. Simulation results show the validity of the proposed method, which can efficiently reconstruct the unambiguous signal for GEO-LEO bistatic SAR. [ABSTRACT FROM AUTHOR]

This letter presents a new approach of digital elevation model generation using circular synthetic aperture radar. The approach is composed of two steps, target separation and height estimation. In step 1, subaperture images are reshaped into vectors and stacked to build a composite matrix. The composite matrix is decomposed into a low-rank matrix and a sparse matrix based on “Semi-Soft Go Decomposition” algorithm. The targets, whose height is equal to the reference imaging height plane, are contained in the low-rank matrix, whereas the targets with other heights are contained in the sparse matrix. In step 2, the sparse matrix is further decomposed into several shifted low-rank matrices, each of which corresponds to the targets sharing one height, based on “Shifted Subspaces Tracking” algorithm. The height of the targets contained in each low-rank matrix is estimated from the shifts of the matrix’s subspaces. The effectiveness of the proposed approach is investigated by the Gotcha public release data set. [ABSTRACT FROM PUBLISHER]

Spaceborne bistatic synthetic aperture radar (SAR) system with an inclined geosynchronous (GEO) illuminator and a low-earth-orbit (LEO) receiver is capable of providing a vast area of surveillance and fine spatial resolution, which presents huge potentials for future earth observation. In this letter, inclined GEO–LEO azimuth multichannel SAR (MC-SAR) system for high-resolution wide-swath imaging is investigated. Starting from modeling geometry of inclined GEO–LEO bistatic MC-SAR, the signal model is analyzed in detail for the first time, and the equivalent positions of the received channels are obtained. Then, we found the spatial-variant residual phase error cannot be compensated accurately by conventional effective phase center (EPC) processing. Moreover, because of the complex bistatic configuration, the frequency-domain imaging algorithms become extremely difficult to achieve a well-focused and phase-preserved image. Meanwhile, the time-domain back-projection algorithm (BPA) faces with a technical challenge due to the nonuniform sampling in azimuth. To address these issues, a bistatic weighted BPA (BWBPA) for GEO–LEO MC-SAR is derived and presented. Without the procedure of EPC, the BWBPA can suppress azimuth ambiguities effectively and yield phase-preserved SAR images. Simulated data results show the validity of the presented method. [ABSTRACT FROM PUBLISHER]

When combined with digital beam-forming (DBF) techniques, multichannel synthetic aperture radar (SAR) systems can achieve high-resolution and wide-swath SAR imaging. However, inevitable channel biases will degrade the performance of DBF in practice. To address this problem, a novel channel phase bias estimation algorithm is proposed in this letter. Theoretical analysis reveals that the signal of the first channel, which is considered as the reference channel, can be reconstructed from the signals of other channels, regardless of noise and signals outside the Doppler bandwidth. In the presence of phase biases, there is a reconstruction error after the cancellation by subtracting this reconstructed signal from the original signal. However, by minimizing the reconstruction error, the channel phase biases can be precisely estimated. The effectiveness of the proposed algorithm is validated by the experimental results. [ABSTRACT FROM PUBLISHER]

In multi‐channel high‐resolution and wide‐swath (HRWS) synthetic aperture radar (SAR) processing, range sampling time errors and phase mismatches severely degrade the reconstruction performance of unambiguous Doppler spectrum. To address this problem, an improved channel mismatch estimation algorithm for multi‐channel HRWS SAR is presented in this Letter. The technique of combining phase wrapping and weighted least‐squares fitting is capable of realising a robust estimation of range sampling time errors and constant phases between adjacent channels. Then, Doppler centroid as well as channel phase mismatches can be estimated from these constant phases based on the theory of spatial cross‐correlation coefficient (SCCC). Compared to the conventional algorithm, the improved performance can be achieved by using the proposed two‐step procedure. The effectiveness of the proposed algorithm is confirmed by experimental results based on airborne real data. [ABSTRACT FROM AUTHOR]

In multichannel high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems, Doppler centroid (DC) is essential for SAR focusing. However, conventional phase-dependent DC estimators for single-channel SAR systems face many problems in multichannel HRWS SAR systems because of the azimuth undersampling of each channel and channel mismatches in phase. To estimate the baseband DC, the spatial cross-correlation coefficients (SCCCs) of multichannel HRWS SAR signals are exploited, and a novel baseband DC estimator named SCCC method is proposed in this letter. Validation of the proposed method is demonstrated with the real airborne multichannel SAR data. [ABSTRACT FROM PUBLISHER]

This Letter proposes a high‐precision and non‐iterative polarimetric synthetic aperture radar (SAR) (PolSAR) calibration algorithm. By solving a system of non‐linear equations, the distortion parameters can be obtained directly. The proposed algorithm is assessed by the simulated PolSAR data. The experimental results show that the algorithm can accurately solve all distortion parameters even though the crosstalk is high and has a better estimation performance compared with the widely used non‐iterative Quegan algorithm. [ABSTRACT FROM AUTHOR]

This article concerns the analysis and compensation of track deviations in high-resolution automobile synthetic aperture radar (SAR). We establish the geometry in which the automobile-SAR raw data is acquired. Based on the derived model, the research investigates the impact of track deviations on the final focused image quality and we propose a motion compensation strategy which can be applied to obtain a well-focused SAR image. This article presents how to obtain the accurate positions of the antenna phase centre using the velocity and attitude angles measured by inertial navigation system/global positioning system, and proposes a new method to compensate for forward velocity errors which are decomposed into two components and compensated individually, that is, high-order and low-order phase compensation. Finally, the results from both simulated data and real data are presented to validate the whole analysis and the proposed procedure. [ABSTRACT FROM PUBLISHER]

Incorporated with digital beam-forming processing, multichannel spaceborne synthetic aperture radar (SAR) systems are able to overcome the minimum antenna area constraint and yield high resolution and wide swath (HRWS) images. This letter mainly investigates the performance of the space–time adaptive processing (STAP) approach applied to HRWS SAR imaging. The analytic expressions for the signal-to-noise ratio (SNR) scaling factor and azimuth ambiguity to signal ratio (AASR) are derived and confirmed by the simulated results. Then, the influence of channel errors on HRWS imaging is analyzed in detail. [ABSTRACT FROM PUBLISHER]

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar (SAR) systems are promising in high-resolution wide-swath imaging. However, the mismatch among channels will degrade the performance of DBF. In this letter, two novel methods are proposed to estimate channel errors for multichannel SAR systems in azimuth. The first method is based on the fact that the space spanned by the signal eigenvectors is equal to that spanned by the practical steering vectors. In the second method, the channel errors are directly estimated by the antenna patterns without matrix decomposition and inversion processing. Both the theoretical analysis and experiments demonstrate the effectiveness and efficiency of these two methods. [ABSTRACT FROM PUBLISHER]

Multibaseline phase unwrapping is a critical processing procedure of multibaseline synthetic aperture radar interferometry (InSAR). It has an advantage over single-baseline phase unwrapping in discontinuous-terrain-height estimation. In this paper, the pixels' combination information of multiple InSAR interferograms with different baseline lengths is deeply investigated, and the term ambiguity vector is proposed to represent a pixel's ambiguity number of multiple interferograms. It is also revealed that pixels with the same ambiguity vector have an exclusive pattern among them. A fast cluster-analysis (CA)-based method is proposed for multibaseline phase unwrapping. In this method, all pixels are first clustered into different groups according to their patterns, and then, information of the cluster center is used to unwrap the phases of pixels group by group. Simulation results are shown to verify the effectiveness, efficiency, and noise robustness of CA multibaseline phase-unwrapping method. [ABSTRACT FROM AUTHOR]

A new approach is presented to estimate the fringe frequencies in interferometric synthetic aperture radar (InSAR) phase image. A first-order model is usually used for fringe frequency estimation, but in steep regions or low-correlation regions, it often fails. In this letter, a prefiltered interferogram, obtained by the slope-compensated or conventional mean filter, is divided into small patches and unwrapped separately. Subsequently, we differentiate the local-phase-unwrapping results to obtain the fringe frequencies. Furthermore, the invalid fringe frequencies are eliminated by a statistical threshold. Finally, the interferogram is filtered by compensating the estimated fringe frequencies in the averaging window of the mean filter. The proposed method can obtain continuous fringe frequency estimation, and it is not constrained by the first-order model. The effectiveness of the proposed approach is verified by the simulated and real InSAR data. [ABSTRACT FROM PUBLISHER]

By applying digital beam‐forming (DBF) technique, the along‐track multi‐channel synthetic aperture radar (SAR) system can simultaneously achieve high‐resolution and wide‐swath (HRWS) imaging. However, the presence of unavoidable phase biases tends to degrade the DBF performance. To address this issue, a novel phase bias estimation algorithm based on Doppler spectrum optimisation is proposed. By exploiting the fact that phase bias would cause Doppler spectrum broadened, the phase biases can be successfully estimated by maximising a sharpness optimisation of the Doppler spectrum. The effectiveness of the algorithm is validated by experimental result carried out on the SAR data collected by an air‐borne multi‐channel system. [ABSTRACT FROM AUTHOR]

3D scene reconstruction from single‐pass circular synthetic aperture radar (CSAR) data has been a research hot spot in various remote sensing applications. Among existing literature, radargrammetry techniques and model assistant methods are two dominant approaches. However, the performance of these methods is limited in practical applications: radargrammetry techniques obtain merely one height value along vertical; model assistant approaches only work when valid models are given. A single‐pass CSAR 3D scene point cloud reconstruction method is proposed. First, the connection between an object and its projections in multi‐aspect SAR images is established with no auxiliary model. On the basis of the connection, voxels are classified into inner voxels (voxels beneath the target profile) and outside voxels (voxels outside of the target profile). Discarded all the outside voxels, the remained inner voxels are combined to form the 3D point cloud of the target. It is similar to the sculpturing process from a raw material to a piece of craft. Finally, a 3D scene is retrieved through assembling all reconstructed targets into a unified coordinate system. The feasibility of the proposed method is validated by the Gotcha Volumetric SAR Data Set. [ABSTRACT FROM AUTHOR]

In this paper we investigate the possibility to produce high‐resolution synthetic aperture radar (SAR) images of wide areas from the data collected by the distributed small spaceborne SAR systems. In particular, we focus on the data processing techniques for overcoming the Doppler ambiguity effects characterizing ground echoes and achieving high‐resolution SAR images of wide areas. A novel approach is proposed, the key idea of which is to retrieve the unambiguous azimuth wide (full) spectrum signal from the received ground echoes by using a space–time adaptive processing (STAP) algorithm to overcome the Doppler aliasing effect induced by the lower pulse repetition frequency (PRF); following this operation, conventional SAR data processing tools can be applied to fully focus the SAR images. The STAP‐based approach has the advantages of simplicity, robustness and high efficiency. We also discuss the array configuration requirements, and give a platform velocity/PRF criterion for array configurations. [ABSTRACT FROM AUTHOR]

Polarimetric SAR (PolSAR) scattering characteristics of imagery are always obtained from the second order moments estimation of multi-polarization data, that is, the estimation of covariance or coherency matrices. Due to the extra-paths that signal reflected from separate scatterers within the resolution cell has to travel, speckle noise always exists in SAR images and has a severe impact on the scattering performance, especially on single look complex images. In order to achieve high accuracy in estimating covariance or coherency matrices, three aspects are taken into consideration: (1) the edges and texture of the scene are distinct after speckle filtering; (2) the statistical characteristic should be similar to the object pixel; and (3) the polarimetric scattering signature should be preserved, in addition to speckle reduction. In this paper, a joint restriction principle is proposed to meet the requirement. Three different restriction principles are introduced to the processing of speckle filtering. First, a new template, which is more suitable for the point or line targets, is designed to ensure the morphological consistency. Then, the extent sigma filter is used to restrict the pixels in the template aforementioned to have an identical statistic characteristic. At last, a polarimetric similarity factor is applied to the same pixels above, to guarantee the similar polarimetric features amongst the optional pixels. This processing procedure is named as speckle filtering with joint restriction principle and the approach is applied to GF-3 polarimetric SAR data acquired in San Francisco, CA, USA. Its effectiveness of keeping the image sharpness and preserving the scattering mechanism as well as speckle reduction is validated by the comparison with boxcar filters and refined Lee filter. [ABSTRACT FROM AUTHOR]

High accuracy in complex images coregistration is essential in ground moving target indication (GMTI) processing of synthetic aperture radar (SAR) data, normally termed SAR-GMTI. The clutter suppression performance is proportional to the coregistration accuracy. In this correspondence, we propose a new SAR-GMTI approach, which is robust to the SAR images coregistration error. The observed clutter-plus-noise vector is built using the neighboring pixels as the first step, thus the corresponding covariance matrix, termed as joint covariance matrix, can be estimated. The joint noise subspace is obtained by eigen-decomposing of the joint covariance matrix. The clutter is suppressed successfully by a projecting operation, i.e., a projection of the joint observed vector into the resulting joint noise subspace. The information of neighboring pixels is substantially exploited in the clutter suppression, resulting in the robustness, even at the presence of large coregistration error. Both the simulated and real multi-channel airborne data are used to validate the proposed approach. [ABSTRACT FROM PUBLISHER]