Wide-angle staring synthetic aperture radar ground moving target indication (WasSAR-GMTI) has garnered attention due to its capability to monitor a stationary area over an extended period and ability of tracking moving targets. Recently, the research on moving target trajectory reconstruction has also raised interest. However, the low positioning accuracy and impractical assumption of traditional method which makes it can hardly practical application. We propose a novel precise trajectory reconstruction of moving target in this paper. First, we segment the echo into subapertures, after clutter rejection and radial velocity estimation, quasi-maximum likelihood (QML) is applied to estimate polynomial phase signal (PPS) parameters of phase history. And then, Levenberg-Marquardt (LM) algorithm is applied to decouple the motion parameters. Based on the motion parameters, the coarse trajectory can be reconstructed. After that, the envelope history of moving target is extracted. Modeling the motion trajectory of the moving target in segments and estimate the trajectory of each segment using the corrected envelope history and coarse trajectory. Finally, after processing all segments, the precise trajectory of moving target is obtained. The effectiveness and practicability of the proposed algorithm were demonstrated by the processing results of experimental WasSAR data.

Wide-angle staring synthetic aperture radar ground moving target indication (WasSAR-GMTI) has been widely recognized for its long-term observation capabilities of fixed areas and its achievement in moving target tracking. Recently, the research on moving target trajectory reconstruction has also raised interest. However, the neglect of height-dimensional information makes it difficult to apply in the scene with terrain undulation. In this paper, a three-dimensions (3-D) trajectory reconstruction method with L-antenna which combines interferometry SAR (InSAR) and GMTI technique is proposed. Meanwhile, it’s the first time that L-antenna is applied in 3-D geo-location of moving target. Firstly, the echo is segmented into several sub-apertures and the lever arm compensation and back projection (BP) imaging are required to register the multi-channel images. Secondly, the along-track multi-channel is processed which contains clutter rejection and radial velocity estimation. Thirdly, the cross-track interferometric phase extraction is proposed and 3-D geo-location of moving target is estimated. Apart from extracting height-dimensional information from interferometric phase directly, a method based on digital elevation model (DEM) is also proposed. And the comparison of the two methods is given in this paper. The processing results of real data have confirmed the efficacy and practicality of the proposed algorithm.

The Wide-Angle Stare Synthetic Aperture Radar (WasSAR), as an emerging SAR observation mode, enables long-duration, multi-angular imaging of a scene, demonstrating remarkable advantages in three-dimensional (3D) information acquisition. A critical step in the process of 3D information extraction lies in accurately determining the displacement information between sub-aperture images captured from adjacent azimuth angles. During the WasSAR imaging process, spatial targets exhibit positional discrepancies in imaging results obtained from different azimuth perspectives, making pixel-wise displacement estimation in SAR images highly challenging, especially in complex scenarios. To address this challenge, this study proposes an innovative displacement estimation method for WasSAR imagery tailored for 3D information extraction. The proposed approach begins with brightness equalization preprocessing to harmonize the brightness distribution between two images, ensuring the accuracy of subsequent processing steps. This is followed by an initial estimation using block-based registration techniques based on the Enhanced Correlation Coefficient (ECC). Finally, an improved optical flow algorithm is employed to achieve precise displacement estimation, significantly enhancing the accuracy and reliability of displacement information estimation between SAR images. A series of experiments were conducted using Ku-band Mountain scene datasets acquired by the National University of Defense Technology. The experimental results include a comprehensive comparative analysis with several existing displacement estimation methods, showcasing the superior performance of the proposed algorithm across multiple key performance metrics. The proposed algorithm’s performance in 3D information extraction applications was also evaluated, confirming its effectiveness and high practicality.

Synthetic aperture radar (SAR) multiview observations can acquire omnidirectional scattering characteristics of targets, providing richer information for target detection and recognition. Deep learning has been widely applied to SAR image interpretation in recent years. However, the sensitivity of SAR images to imaging parameters and the limited training samples pose challenges in applying deep learning to SAR target detection. Therefore, this article first designs an SAR omnidirectional subaperture division data enhancement method with different aspect accumulation angles, multilook numbers, and subaperture overlap angles based on SAR imaging parameters and the original echo. Meanwhile, an omnidirectional SAR target detection dataset called SAR-Vehicle-Det is constructed using this subaperture division method to evaluate the model performance. Then, this article proposes a novel network attributed scattering center (ASC)-U2Det based on ASC guidance for SAR target detection. The prediction is divided into the ASC reconstruction image branch and the target detection branch. The reconstruction branch uses ASC reconstruction mask maps to guide the network to extract the SAR target scattering features at different aspect angles, suppress the background clutter interference, and improve the detection accuracy of the target detection branch. Finally, this article also evaluates the impact of imaging parameters with different subaperture accumulation angles and multilook numbers on the network detection performance. Experiments on the SAR-Vehicle-Det and miniSAR datasets show that the proposed ASC-U2Det outperforms many existing target detection algorithms.

In order to adapt to various detection environments on the ground, airborne synthetic aperture radar (SAR) as a remote sensing platform usually arcs along nonlinear trajectories, and the large accumulation angle in the circling process also improves the imaging effect. However, the arc motion demands rigorous control of the flying platform and precise measurement of the motion. In some cases, there is a significant discrepancy between the track recorded by the flight platform and the actual track, which not only affects the imaging effect but also interferes with the positioning and navigation of the platform. This article presents a new method of arc-line SAR positioning and imaging based on a closed-loop structure. The echo history extracted from a 1-D range profile is corrected using an echo-history correction factor (EHCF), which reduces the self-positioning error of the platform caused by the motion measurement device. This allows for accurate positioning of the flying platform and the acquisition of imaging results with superior focusing performance. The effectiveness and stability of the proposed method are proven by simulation and experimental results.

Circular synthetic aperture radar (CSAR) has garnered a lot of attention because of its exceptional capabilities. However, CSAR imaging is sensitive to terrain undulation errors due to the curved trajectory. The projection of an object whose height deviates from a reference height (RH) forms a circular ring in the full-aperture image. Presently, error compensation using a digital elevation model (DEM) is a prevalent solution to this issue. Although DEM can be inverted from echo data, the accuracy is unsatisfactory. Inspired by optical multi-focus image fusion methods, a CSAR multi-layer focusing imaging method is proposed in this letter. Firstly, CSAR sub-aperture images are used to construct multi-layer focusing images by displacement compensation, which is more efficient than applying an imaging algorithm directly. Secondly, the multi-focus image fusion method is applied to obtain a fully focusing image. Finally, the decision maps are used to invert the target region’s DEM. The multi-layer focusing imaging method can make objects of different heights focused. The fused result is fully focused and has a resolution of 1 m, depending on the CSAR system. The inverted DEM can visually describe the objects’ contours. Experimental results demonstrate the effectiveness and practicability of the proposed method.

As a new observation mode, wide-angle staring synthetic aperture radar ground moving target indication (WasSAR-GMTI), which can observe the fixed area for a long time and achieve moving target tracking, has attracted a lot of interest. However, with increasingly complex flight trajectories and application scenarios, the performance of traditional method tends to degrade. In this article, a novel approach based on post-Doppler space-time adaptive processing (PD-STAP) and imaging method is proposed. First, selecting and extending training data from repeat-pass data can obtain accuracy estimated clutter covariance matrix (CCM). Moreover, the relationship between extended quantity of training data and clutter suppression performance is further analyzed in this article, and then, the joint-pixel PD-STAP (JP PD-STAP), which utilizing auxiliary units under test cell along range direction, is performed to overcome the effect of residual range curvature after keystone transform (KT). Finally, after clutter suppression, the parameters and imaging method based on WasSAR system are proposed. The multidimensional parameter is simplified as 1-D line search problem, which has high efficiency. Considering the curvilinear trajectory, the back-projection (BP) is adopted to process. Inserting parameters into BP can be seen as coarse motion compensation (MOCO), and the further spectrum compression (SC) method and phase gradient autofocus (PGA) is performed to obtain refocus and relocate imaging of moving target. The real-measured WasSAR data processing results demonstrated the effectiveness and practicability of the proposed algorithm.

A unique mode known as wide-angle staring synthetic aperture radar ground moving target indication (WasSAR-GMTI) allows for the dynamic surveillance of moving targets over a wide range of azimuth angles. Despite WasSAR-GMTI develops rapidly, the parameter estimation and trajectory reconstruction of moving target in a three-Dimensional (3-D) field have not been solved well in WasSAR. In order to address this problem, a framework based on 3-D velocities’ and 3-D positions’ estimation is proposed in this article. On account of the derived equivalence, it is possible to characterize moving targets in WasSAR-GMTI and achieve the decoupling of velocity and position. First, for the multidimensional velocities’ estimation, the joint interferometric phases of several subapertures are utilized. Then, to estimate the multidimensional positions, the signal of moving target in WasSAR is modeled as a polynomial-phase signal (PPS). We tackle the issue of 3-D positions’ estimation through the coefficients of PPS estimated by cubic phase function (CPF) method. Finally, 3-D trajectory reconstruction of moving target is accomplished by combining the results of multiaperture estimation. The proposed method extends the parameter estimation to the 3-D case, and the applications of WasSAR-GMTI are spread. Moreover, the parameter estimation of moving target is addressed independently, namely without auxiliary information of priori road detail. The estimation accuracy of the proposed method is evaluated by the simulated data, and the validity and feasibility of the proposed method are demonstrated through the results of real data.

For airborne repeat-pass synthetic aperture radar interferometry (InSAR), residual motion errors (RMEs) exist between the true and measured trajectories due to the inaccuracy of current navigation systems. In addition, a global unknown phase ambiguity (PA) exists in the unwrapped phase due to the error of absolute phase estimation. The RME and PA are significant error sources in the repeat-pass InSAR, which can cause phase errors in the final interferograms. In general, an external digital elevation model (DEM) can be used to estimate the RME and PA. However, it is hard to find a high-precision external DEM matching with the airborne InSAR data. Compared with the traditional InSAR technique, the 360° aperture gives circular InSAR (In-CSAR) the capability to estimate the RME and PA without external DEMs. Unlike previous approaches, in this article, a multiangle observation model is established to estimate RME and PA simultaneously. This model registers the DEM images obtained from different observation angles. In the field of image registration, the Demons algorithm is often used for nonrigid registration. We use, for the first time, the Demons algorithm to register multiangle false DEM images containing height errors and obtain the reference DEMs. Due to the gradient of the DEM image being destroyed by the RME and PA, a two-step preprocessing is proposed to achieve subpixel registration of multiangle false DEM images. After obtaining the reference DEM, the least square (LS) or robust mixed integer linear programming (RMILP) can estimate the unknown RME and PA. The results show that, with respect to the true values, the root-mean-square error (RMSE) of the calibrated DEMs is 0.37 m for the simulated dataset and 1.17 m for the real dataset. After correcting the RME-induced and PA-induced height errors, the RMSE of the DEM is improved by at least 92.6% for the simulated dataset and by at least 70.8% for the real dataset.

The acquisition of 3-D information in the observation scene has always been a prominent issue in the field of synthetic aperture radar (SAR). The emerging wide-angle staring SAR (WasSAR) utilizes its unique multiview observation performance to obtain offset information of the target position under different observation angles, enabling the acquisition of 3-D information of the observation scene. However, existing multiview 3-D information extraction methods suffer from large errors due to a lack of prior information about the observed scene. In order to address these challenges, this article analyzes the impact of the missing incidence angle information on the 3-D reconstruction results and proposes a 3-D information correction algorithm. The method only needs the single-channel echo information of the two azimuth angles of a single pass and the corresponding radar platform motion information and does not need to rely on any a priori information of the observation scene, which realizes the acquisition of 3-D information without a priori information in the real sense. Through simulation experiments, we quantitatively analyze the error transfer coefficient and confirm both accuracy and effectiveness through experimental data processing in Ku-band mountain scenes autonomously measured by our team. The proposed algorithm significantly enhances measurement precision and reliability, demonstrating a mean error reduction to just 49% and a root-mean-square error (RMSE) decrease to 46% compared to the traditional method, thereby confirming its superior performance and practicality.

The low-band synthetic aperture radar (SAR) is a system that can present foliage-penetrating (FP) targets and exposed strong-scattering targets while the high-band SAR system can present exposed targets and texture information except for FP targets. Therefore, the different features of co-registered low-band and high-band SAR images can theoretically reveal FP targets with some disturbances. However, the co-registered dual-band SAR images cannot do the difference operator directly for the distinct statistical property of the SAR image pair. The traditional method is to transfer the background texture from the high-band SAR image to the low-band SAR image by the cycle-consistent generative adversarial network (CGAN) method. However, CGAN would generate discontinuity and mistakes in transferring the large-scale texture information, and the complex network would heavily increase the time complexity of the application. To overcome this issue, we first innovatively introduce a fast and accurate texture-transferring method based on the dual-band SAR image fusion (DBIF), then we further combine the DBIF-based texture-transferring method with the difference operator and the threshold segmentation, and finally we get a novel DBIF-based FP target detection (DBIFFPTD) method. To verify the feasibility of the DBIF-based texture transfer method, we discuss the reflection form of different landscape objects at dual-band waves and estimate the theoretical texture transferring the image. Experiments on the open dual-band AIR-MD-SAR dataset and the independently measured dual-band SAR dataset show that the novel DBIF performs better than CGAN in transferring texture information of dual-band SAR images. Besides, dual-band linear SAR (LSAR) and circular SAR (CSAR) FP experiments are both conducted to show that the proposed DBIFFPTD has wide applicability in the flight track and is superior to the traditional low-band double-parameter constant false alarm rate (DCFAR) detector-based FPTD (DCFARFPTD) method and the dual-band CGAN-based FPTD (CGANFPTD) method.

The performance of multi-channel synthetic aperture radar (SAR)-based ground moving target indication (GMTI) is inevitably restricted by channel imperfections and imbalances, and channel calibration procedure is incorporated into the scheme accordingly. The adaptive two-dimensional calibration (A2DC) algorithm is sensitive to outliers and suffers from correction errors. To solve the problem, a modified A2DC (MA2DC) algorithm is proposed in this letter. By improving Doppler calibration model, the proposed MA2DC is more robust than the A2DC algorithm. It can effectively suppress clutter while maintaining detailed features of moving targets, after which the detection capability of moving targets in SAR-GMTI is improved. Its performance is demonstrated by the Gotcha data, which is publicly released by Air Force Research Laboratory.

Multi-channel wide-angle staring synthetic aperture radar ground moving target indication (WasSAR-GMTI) has attracted a lot of interest for its ability of moving target detection and trajectory reconstruction. However, the parameter estimation of moving target is easily affected by clutter and noise which deteriorate the performance of the following geo-location. In this paper, a novel approach for trajectory reconstruction of moving target based on road line is proposed. Firstly, after performing multi-channel calibration, a novel Doppler centroid estimation and correction method is proposed. This method is not depended on attitude information of platform, nor does it require scene uniformity as a prior condition, which has high robustness in complex environment. And then, the weighted adaptive matched filtering (WAMF) and modified Gaussian mixture probability hypothesis density (GMPHD) is performed for velocity estimation and tracking. Last, the error items affecting geo-location accuracy were analyzed in detail. And a novel two-step geo-location method based on road line is proposed to correct geo-location error which can be applied in complex road network. The proposed method only needs one-dimensional parameter searching which has high efficiency. The real-measured WasSAR data processing results demonstrated the effectiveness and practicability of the proposed algorithm.

Ground moving targets with complex motions often appear seriously dislocated and smeared in synthetic aperture radar (SAR) imagery due to non-cooperative motion. Refocusing such targets in SAR is challenging because of unknown motion parameters. In this paper, a novel SAR moving target imaging method based on adaptive phase tracking (MTIm-APT) is proposed. First, the Hough transform (HT) and the second(2nd)-order Keystone transform (SOKT) are performed to correct the range migration. Second, the Doppler phase can be adaptively tracked based on the improved extended Kalman filter (EKF). With the tracked Doppler phase, the motion parameters required for moving target imaging is estimated. Finally, the moving target is well-focused after motion parameters compensation since the high-order Doppler phase errors are efficiently eliminated. Unlike existing research that only considers the 2nd- or third(3rd)-order Doppler phase, the proposed method considers higher-order Doppler parameters which can be simultaneously estimated, thus eliminating error propagation effect. More importantly, due to the suboptimal filtering characteristics of EKF, the proposed method maintains excellent imaging performance at lower signal-to-noise ratio (SNR) than classical PGA. On the other hand, our method has a certain advantage in computational efficiency. Both simulated and real data processing results are provided to validate the feasibility and effectiveness of the proposed SAR MTIm-APT method.

Isotropy edge detection filters for synthetic aperture radar (SAR) images, such as crater-shaped window (CSW), cannot keep both high edge resolution and good speckle suppression ability at the same time. In this letter, an edge detector-combined CSW and robust inhibition-augmented curvilinear operator (RUSTICO) has been proposed. First, the preliminary edge strength map (ESM) is calculated by using CSW. Second, the RUSTICO is applied to suppress the influence of speckle and obtain the improved ESM (IESM). Moreover, by using nonmaximum suppression and hysteresis thresholding on IESM, the one-pixel-wide edges are acquired. Finally, the missing edges at intersection areas are extracted by the linking method. The experimental results on simulated and real SAR images demonstrate that the proposed edge detector can yield accurate and integrated edge map.

Road extraction is an important part of synthetic aperture radar (SAR) image interpretation. In recent years, circular SAR (CSAR) has attracted extensive attention from researchers owing to its ability of 360° observation. Due to the unique imaging geometry of CSAR, CSAR images contain more complete road information. However, the curvilinear-structured appearance of roads in CSAR images and the complexity of the scene result in difficulties in road extraction. The curvilinear structure detector (CSD) is capable of extracting the curvilinear structures with a specific width from complicated image scenes. Based on the traditional CSD, an improved CSD (ICSD) for local road area extraction from CSAR images is introduced in this article. First, by adopting ICSD, the edges of a CSAR image and centerlines of local roads are extracted, as well as their direction. Second, the local roads are obtained by geometrical and radiometrical rules. Finally, the missing intersections and edge pixels are repaired to acquire high-precision and high-quality extraction results of the local road area. The experimental results on different band CSAR images reveal that the proposed method exhibit enhanced performance than the three state-of-the-art methods.

For synthetic aperture radar (SAR) images, there are many defocused moving targets with azimuthal deviation. Ground moving target indication (GMTI) is developing rapidly to detect moving target for traffic surveillance and military vehicle tracking. In this paper, multi-channel SAR-GMTI technology is studied and a moving target detection method based on clutter suppression interference (CSI) and relaxation-based cyclic (RELAX) is proposed to detect moving target efficiently and accurately, the time of which is only 0.22% of the time by global RELAX. Combined with multi-channel signals, CSI is performed to detect targets of interest. Then, RELAX is applied to further reduce false alarm and estimate radial velocity for geolocation. Experimental SAR data processing results show that the method is effective for moving target detection and parameter estimation.

Since the circular track synthetic aperture radar (CSAR) could observe the target scene in all directions, it can perform three-dimensional imaging of the target area. When using the sub-aperture sequence to extract the digital elevation model (DEM) of the target scene, in order to be able to reasonably use the correlation between the sub-apertures in the arc to improve DEM extraction accuracy, this paper proposes a method to extract DEM information using the correlation between sub-apertures. By using the feature of stronger correlation between adjacent sub-apertures, the accuracy of DEM extraction is effectively improved. Finally, it was verified by quoting the measured data to verify the feasibility and accuracy of the algorithm.

Circular synthetic aperture radar (CSAR) observes the scene by 360 degrees, the characteristics of targets from different aspects can be obtained. The noncoherent imaging is more popular since more textural features and lower speckle noise can be acquired. However, due to the motion error of the radar platform and the topography of observation scene, the noncoherent imaging result of full aperture can not be derived by simply noncoherent superimposing the subaperture images. In this paper, based on the enhanced correlation coefficient (ECC), we proposed a registration strategy to obtain full aperture noncoherent imaging result of CSAR, and the experiments demonstrate the effectiveness of our method.

Holographic synthetic aperture radar (HoloSAR) tomography is an attractive imaging mode that can retrieve the 3-D scattering information of the observed scene over 360° azimuth angle variation. To improve the resolution and reduce the sidelobes in elevation, the HoloSAR imaging mode requires many passes in elevation, thus decreasing its feasibility. In this article, an imaging method based on iterative adaptive approach (IAA) and generalized likelihood ratio test (GLRT) is proposed for the HoloSAR with limited elevation passes to achieve super-resolution reconstruction in elevation. For the elevation reconstruction in each range-azimuth cell, the proposed method first adopts the nonparametric IAA to retrieve the elevation profile with improved resolution and suppressed sidelobes. Then, to obtain sparse elevation estimates, the GLRT is used as a model order selection tool to automatically recognize the most likely number of scatterers and obtain the reflectivities of the detected scatterers inside one range-azimuth cell. The proposed method is a super-resolving method. It does not require averaging in range and azimuth, thus it can maintain the range-azimuth resolution. In addition, the proposed method is a user parameter-free method, so it does not need the fine-tuning of any hyperparameters. The super-resolution power and the estimation accuracy of the proposed method are evaluated using the simulated data, and the validity and feasibility of the proposed method are verified by the HoloSAR real data processing results.

Displaced phase center array (DPCA) and along-track interferometry (ATI) have been widely used for ground moving target indication (GMTI) in multi-channel circular synthetic aperture radar (CSAR) system. In ideal conditions, these methods can suppress background clutter effectively. However, the nonideal movement of platform may create a nonzero crab angle, which will induce a cross-track baseline offset and affect GMTI processing seriously. This letter analyzes the influence of crab angle on interferometric phase theoretically. Here, we propose a two-step phase calibration method to greatly improve the performance of CSAR-GMTI by eliminating the range-varying phase error. This method is independent of imaging and GMTI processing. Simulated and measured data results verify the correctness of the theoretical analysis and the validity of the proposed method.

By introducing curvilinear structures extraction (CSE) instead of watershed algorithm (WA) or nonmaximum suppression (NMS) to edge strength map (ESM), an improved ratio of exponentially weighted averages (ROEWA) edge detector with better capacity for weak edges detection is proposed to extract smooth edges and edge direction of synthetic aperture radar (SAR) images. Using the ROEWA, the ESM is calculated. Then the CSE algorithm is employed to extracted edges, by acquiring eigenvectors and eigenvalues of the Hessian matrix, the improved ESM (IESM) is obtained, which ensures the good weak edge detection capacity and smoothness of edges. Experimental results on simulated and real SAR images show that the improved ROEWA based on CSE attains better performance than the one using WA or NMS.

The ultrahigh frequency ultra-wideband synthetic aperture radar (UHF UWB SAR) has the well foliage penetrating and high-resolution imaging, which can be used to detect the concealed area under the foliage in forests. This paper presents an airborne UHF UWB SAR experiment and imaging results. During the winter, an airborne campaign has been carried out in Shanxi Province in China, and the raw data was collected. In this experiment, the SAR system was integrated onboard a CESSNA-172 airplane. The antenna was fixed on the suspension arm of the right wing of the airplane, while the other part of the SAR system was placed on the back seat of this airplane. The experimental results have been obtained from the collected raw data, which proved the imaging performance of the airborne UHF UWB SAR system as well as the validity of the imaging method.

Holographic synthetic aperture radar tomography can realize full 3-D reconstructions of objects over 360° with very high resolution, and thus becomes an interesting 3-D imaging technique. However, due to the uncompensated platform motion errors, phase errors among different tracks usually exist in this imaging mode, which will hinder the 3-D image focusing. In this letter, a phase calibration method based on phase gradient autofocus is proposed to mitigate the influence of these phase errors. It exploits the space-invariant characteristic of the phase errors in a limited scene and uses an efficient and robust multibaseline autofocus to calibrate the phase errors among the multiple circular tracks. Experimental results with the GOTCHA real data are carried out to demonstrate the validity and feasibility of the proposed method.

Synthetic aperture radar (SAR) ground moving target indication (GMTI) has attracted a lot of interest from researchers for its ability of simultaneously obtaining high-quality images of stationary scenes and detection of moving targets. In recent years, the research on moving target tracking besides detection by using SAR-GMTI has also raised interest. Compared with standard SAR, the long observation time of circular SAR (CSAR) makes it possible for moving target trajectory reconstruction. By using a prior knowledge of the road information, an effective method for moving target trajectory reconstruction in single-channel CSAR is proposed in this paper. First, the radar echo is segmented according to subapertures, and the Doppler filtering is performed on each subaperture echo for clutter suppression. Second, the range walk induced by target motion is compensated by the keystone transform, and trajectories in range–Doppler domain are obtained. Last, the moving target trajectory in ground coordinate is reconstructed by using the dynamic programming algorithm with road information restrain. Experimental SAR data processing results show that the method is effective for the moving target trajectory reconstruction.

Since the trajectory deviations of a radar platform cause serious phase errors that degrade the focusing quality of synthetic aperture radar (SAR) imagery, an autofocus method is very important for high-resolution airborne SAR imaging. In this letter, an extended autofocus backprojection (EABP) algorithm is developed to accommodate the phase errors. Under the criterion of maximum image sharpness, the traditional ABP algorithm supports a broader class of collection and imaging geometries. However, it neglects the influence of SAR image energy distribution on the estimation of phase errors that make it inapplicable for SAR imaging, which has high dynamic range, such as low-frequency SAR imaging. By choosing regions and balancing the energy distribution of the data, the EABP algorithm is more efficient and useful to avoid the estimation error caused by the unbalanced energy distribution. Its performance has been demonstrated by using the experimental data that are acquired by a P-band airborne SAR system with a low-accuracy global positioning system.

The ultrawideband (UWB) bistatic forward-looking synthetic aperture radar (BFSAR) can realize the high-resolution imaging in the forward direction of the transmitter/receiver, so it has significant applications in both civil and military fields. However, compared to the general narrowband side-looking bistatic synthetic aperture radar systems, the UWB BFSAR systems have larger fractional signal bandwidth and more special acquisition geometry, which will affect the behavior of spatial resolutions. Current methods for spatial resolution analysis of the UWB BFSAR are unsuitable because they do not consider the effects of these two special issues. This letter analyzes the special behavior of spatial resolutions in the UWB BFSAR, and the straightforward gradient method is utilized and extended based on the analysis to calculate the spatial resolutions. The theoretical analysis shows that the range resolution can be calculated by the traditional gradient method directly but the Doppler resolution should be calculated by the extended method. Simulated results verify the correctness of the theoretical analysis and the validity of the proposed method.

Two-dimensional phase unwrapping (PU) is a crucial processing step of synthetic aperture radar interferometry (InSAR). With the rapid advance of InSAR technology, the scale of interferograms is becoming increasingly larger. When the size of the input interferogram exceeds computer hardware capabilities, PU becomes more problematic in terms of computational and memory requirements. In the case of “big-data” PU, the input interferogram needs to be first tiled into a number of subinterferograms, unwrapped separately, and then spliced together. Hence, whether the PU result of each subinterferogram is consistent with that of the whole interferogram is critical to the large-scale PU process. To effectively solve this problem, the L1-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L1-norm PU solutions, is put forward and proved. Furthermore, the L0-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L0-norm PU solutions, is also proposed and proved. Afterward, based on these two theorems, two tiling strategies are put forward for the large-scale L0-norm and L1-norm PU methods. In addition, this paper presents the concepts of the tiling accuracy and the tiling resolution, which are the criteria used to evaluate the effectiveness of a tiling strategy, and we use them to quantitatively analyze the aforementioned tiling strategies. Both theoretical analysis and experimental results show that the proposed tiling strategies are effective for the largescale L0-norm and L1-norm PU problems.

In the last few years, interest in circular synthetic aperture radar (CSAR) acquisitions has arisen as a consequence of the potential achievement of 3D reconstructions over 360° azimuth angle variation. In real-world scenarios, full 3D reconstructions of arbitrary targets need multi-pass data, which makes the processing complex, money-consuming, and time expending. In this paper, we propose a processing strategy for the 3D reconstruction of vehicle, which can avoid using multi-pass data by introducing a priori information of vehicle's shape. Besides, the proposed strategy just needs the single-pass single-polarization CSAR data to perform vehicle's 3D reconstruction, which makes the processing much more economic and efficient. First, an analysis of the distribution of attributed scattering centers from vehicle facet model is presented. And the analysis results show that a smooth and continuous basic outline of vehicle could be extracted from the peak curve of a noncoherent processing image. Second, the 3D location of vehicle roofline is inferred from layover with empirical insets of the basic outline. At last, the basic line and roofline of the vehicle are used to estimate the vehicle's 3D information and constitute the vehicle's 3D outline. The simulated and measured data processing results prove the correctness and effectiveness of our proposed strategy.

Phase unwrapping (PU) is significant in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) data. The classical minimum discontinuity (MD) PU algorithm by Flynn is highly accurate but involves time-consuming computation. To overcome this shortcoming, we proposed a preunwrapping-assisted MD (PAMD) PU method, which has high efficiency and the same unwrapping quality as Flynn's algorithm. In the PAMD method, the phase image is first unwrapped by the preunwrapping algorithm, which generates and optimizes the dipole cuts. The preunwrapping algorithm is fairly fast, and the obtained result is much closer to the optimal solution of MD; therefore, it can be further optimized by Flynn's algorithm efficiently. Tests on simulated and real InSAR data confirm the accuracy and the efficiency of the proposed method.

This paper presents an efficient raw signal generation method based on equivalent scatterer and subaperture processing for the one-stationary bistatic synthetic aperture radar (SAR). It considers the moving platform's motion error to generate the precise raw signal for real SAR systems. First, the imaging geometry in elliptical polar coordinates is built, and then, the scene is divided into several equidistant elliptical rings. Based on the equivalent scatterer model, the approximate SAR system transfer function is derived; thus, each pulse's raw signal is calculated by the convolution of the transmitted signal and transfer function, via the fast Fourier transform (FFT). To further improve the simulation speed, the subaperture and subscene processing is used. The transfer function for the same subaperture's pluses is calculated simultaneously by the weighted sum of all subscenes' equivalent scattering coefficient in the same equidistant elliptical ring, which is performed by the nonuniform FFT (NUFFT). This method only involves the FFT, NUFFT, and complex multiplication, which means the easier operation and higher efficiency. The implementation, limitation, and evaluation of the proposed method are discussed. Simulation results are given to prove the correctness and validity of the proposed method.

Phase unwrapping (PU) for large-scale images is a new challenging problem in reconstructing a digital elevation model from synthetic aperture radar interferometry (InSAR) data. In this letter, we proposed a region-partition-based PU method that could improve the efficiency and decrease the processing memory of the large-scale PU problem for P-band ultrawideband (UWB) InSAR. The interferometric phase is flattened by the reference phase, which is generated from the shift estimation in the registration step. We refer to the residual phase as the misregistration phase (MRP), which corresponds to the error of the shift estimation. The MRP is unambiguous in most of the area with high coherence because of the large fractional bandwidth; thus, the regions that assuredly have the unambiguous MRP are partitioned out from the MRP image and referred to as the high-quality area. Meanwhile, the remaining low-quality areas are separated by the high-quality areas and are considered irregular tiles. After unwrapping the tiles by a minimum discontinuity PU algorithm either in parallel or in series, the full-size unwrapped result is obtained. The test performed on real P-band UWB InSAR data confirms the effectiveness and efficiency of our method.

An extended two-step focusing approach (ETSFA) for processing the squinted spotlight synthetic aperture radar (SAR) data is proposed in this paper. The effect of the squint angle on the azimuth coarse focusing is analyzed and discussed. Based on the analysis results, a nonlinear shift preprocessing method is introduced, which can completely remove the squint angle impacts on the azimuth coarse focusing. Furthermore, based on the squinted spotlight SAR imaging model and the preprocessed echo data, derivations of the azimuth coarse focusing with the deramping-based technique and precise focusing with the modified Stolt-based technique are carried out in detail. Moreover, to produce an acceptable image by the proposed ETSFA for high-resolution ($<$3 m) squinted spotlight SAR with large scene, a subscene processing method is introduced. The experimental results on simulated data prove the validity of the whole analysis and the proposed methods.

In this paper, an extended nonlinear chirp scaling (ENLCS) algorithm for focusing synthetic aperture radar data acquired at high resolution and highly squint angle is proposed. The whole processing of the ENLCS consists of the following three steps. First, a linear range walk correction is used to remove the linear component of target range cell migration (RCM) and to mitigate the range-azimuth coupling of the 2-D spectrum. Second, a bulk second range compression (SRC) is performed in the 2-D frequency domain for compensating the residual RCM, SRC term, and higher order range-azimuth coupling terms. Third, a modified azimuth NLCS (ANLCS) operation is applied to equalize the azimuth frequency modulation rate for azimuth compression. By adopting higher order approximation processing and by properly selecting the scaling coefficients, the proposed modified ANLCS operation has better accuracy and little image misregistration. The overall focusing procedure of the ENLCS algorithm only involves fast Fourier transform and complex multiplication, which means easier implementation and higher efficiency. The experimental results with simulated data prove the effectiveness of the proposed algorithm.