Deep learning-based methods hold significant potential for synthetic aperture radar (SAR) target detection, but they still face numerous challenges, including difficulty extracting global contextual features for large-scale targets, significant multi-scale issues, and the problem of feature extraction of SAR targets with large aspect ratios, which hinder further performance improvement. To this end, this paper proposes a WaveFormer module, which decomposes the image through wavelet convolution and uses convolution and Transformer to process the frequency domain components they are good at, respectively, to expand the receptive field with low parameter overhead and enhance the target feature extraction ability. To address cross-layer information attenuation during feature fusion, a Gather-and-Distribute(GD) mechanism is introduced to reconstruct the Neck network, enhancing multi-scale feature fusion and detection capabilities. Furthermore, given the large aspect ratio and distinct principal axis orientation of SAR targets, a Weighted Strip-Convolution(WSConv) is proposed to effectively improve detection performance. Experiments on the largest multi-class SAR target detection dataset, SARDet-100K, demonstrate that our method achieves a mean average precision (mAP) of 61.5%, reaching state-of-the-art performance and validating its effectiveness.

Synthetic aperture radar (SAR) ship detection faces significant challenges in nearshore scenarios due to strong backscatter interference from land and high ship density. Conventional detectors frequently fail in such environments when land mask information is unavailable. Ports, as hubs of maritime activity, have abundant and accessible SAR data archives, making them ideal testbeds for ship detection studies. Therefore, a two-step spatiotemporal fusion-based detector is proposed, which leverages the spatiotemporal characteristics of ships in SAR time series images. In the first stage, target localization is established through spatial spectrum analysis. In the second stage, difference image analysis is applied to the candidate regions to achieve precise spatiotemporal positioning, enabling effective detection without the need for land masks. An evaluation using a two-year dataset of 60 Sentinel-1A images from the Port of Santos confirmed the method’s effectiveness and superior performance.

The high-resolution wide-swath synthetic aperture radar (HRWS SAR) system enables achieving comprehensive and extensive ground information more accurately and rapidly, enhancing the precision of target detection, identification, confirmation, and description. A common implementation approach of it is azimuth multichannel synthetic aperture radar (SAR), which has become a research hot spot in the field of SAR in recent years. In practice, there is a situation where a channel failure leads to the loss of corresponding data, and in such cases, it is impossible to obtain a high-resolution wide-swath image of quality. Currently, there is no good method to address the data recovery issue for one channel data completely missing. To solve this problem, in this letter, a scheme based on iteration adaptive approach (IAA) and weighted least squares method is proposed for azimuth multichannel SAR missing channel data recovery. Point target simulations and data generated from airborne SAR system demonstrate that the proposed scheme is effective.

The Hongtu-1 (HT-1) synthetic aperture radar (SAR) system is the first spaceborne single-pass multibaseline (MB) interferometric SAR (InSAR) system based on four HT-1 SAR satellites flying in a cartwheel formation. This setup includes three secondary satellites that function as receive-only units to create a compact multistatic SAR system. The primary objective of the HT-1 mission is to generate a consistent global digital elevation model (DEM) at 1:50000 scale. In addition, the HT-1 mission will feature novel SAR imaging technology demonstrations. On March 30, 2023, four HT-1 satellites were successfully launched and started to provide spaceborne radar data services to users. This article provides a detailed description of the HT-1 MB InSAR system, including the SAR performance, the cartwheel formation designed for multistatic SAR data collection with desired baselines, and the uninterrupted synchronization link. The interferometric performance is thoroughly analyzed. With the recorded data, imaging and interferometric processing procedures are introduced, and the capabilities of single-pass MB InSAR DEM generation are demonstrated. Compared with those of ICESAT, the height errors are less than 2 m in flat terrain and less than 5 m in mountainous terrain. Moreover, the resolution and swath of multisatellite mosaic imaging are 3 m and 80 km, respectively. The repeat-pass differential InSAR measurement for surface deformation monitoring is also included.

The Hongtu-1 (HT-1) Synthetic Aperture Radar (SAR) constellation is the first in-orbit spaceborne single-pass multi-baseline interferometric SAR (InSAR) system. The system has the ability to conduct high-resolution earth observation and high-precision, high-efficiency terrain surveying. The highest resolution of the system is better than 0.5 m, and it has a 1:50000 scale global digital elevation model (DEM) and digital surface model (DSM) surveying capability. This paper provides a basic introduction to the HT-1 constellation, and demonstrates the advantages of single-pass multi-baseline InSAR results and its advantages over steep area.

High-resolution wide-swath (HRWS) imaging has always been a primary demand for synthetic aperture radar (SAR) remote sensing. Multiple-input multiple-output (MIMO) is a feasible scheme for achieving HRWS imaging and is a hot research topic among scholars. However, in contrast to classic single-input multiple-output (SIMO) SAR, MIMO-SAR schemes require the isolation of transmitted waveforms. The transmitted waveforms and the corresponding echo separation methods are essential techniques in MIMO-SAR. Orthogonal frequency-division multiplexing (OFDM)-chirp waveforms and an OFDM-beamforming (OB) method have been proposed, but have not been validated experimentally. In this letter, an airborne X-band digital beamforming (DBF)-SAR system is used to demonstrate MIMO-SAR with improved OFDM-chirp waveforms for the first time. Experimental results of frequency- and spatial-domain methods demonstrate that the mixed echoes can be effectively separated by OB scheme. The utilization of bandpass filters (BPFs) in OB scheme can conserve computation resources. Signal-to-interference ratio (SIR) is employed to test the performance of BPFs, where the indicator shows that the SIR loss is within 0.2 dB.

The electromagnetic environment is becoming complex as the usable spectrum will be allocated for more services. As a result of this situation synthetic aperture radar (SAR) missions are frequently perturbed by radio frequency interference (RFI) that jeopardizes their scientific observations all over the world. The state-of-the-art multichannel SAR has anti-RFI capability since it’s capable of digitally modulating the antenna pattern (AP) in postprocessing, thereby steering the null toward the angle of arrival (AOA) of the RFI in the spatial domain. However, the AOA of RFI is space-variant, meaning that the mitigation performance of beamformers sensitive to AOA will greatly deteriorate. In addition, the AOA of in-swath RFI and the target echo arrive simultaneously, thus the traditional beamformer will generate a distorted AP, deteriorating the SAR imagery. In light of these considerations, this article studies the in-swath and out-of-swath RFIs in elevation multichannel SAR and develops their countermeasures. Thereinto, a least$\ell _{1}$-norm model is developed to estimate the AOA of the RFI, followed by two schemes developed to separate the RFI. The former develops a beamformer that joint sidelobe control and null expanding to mitigate the space-variant out-of-swaths RFI, whereas the latter develops a blind source separation (BSS)-based technology to mitigate in-swath RFI, avoiding AP distortion and restoring SAR imagery. The effectiveness of the proposed approaches is supported by experiments based on the measured X-band airborne DBF-SAR data as well as the simulated SAR data.

For azimuth multi-channel (AMC) high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems, non-uniformly sampled signals will lead to false targets appearing in the image, which has a great impact on image quality and target detection. Many spectrum reconstruction methods for stationary scenes have been proposed to obtain images without false targets, but it is ineffective for moving targets due to the phase error caused by radial velocity. To present the radial velocity effect on the reconstructed image clearly, we establish a precise relation between the characteristics (imaging position, residual RCM, and amplitude) of false targets and radial velocity from the Doppler domain perspective. According to the effect analysis, we propose an image-domain false target suppression and radial velocity estimation method for moving targets. First, obtain multiple images through imaging preprocessing. Second, estimate and compensate the phase error of false targets based on the leastL1-norm optimization model to suppress false targets. Third, estimate the radial velocity of real moving targets based on the cross-correlation method. Compared to the existing methods, the proposed method is processed in the image domain which has a high signal-to-noise ratio (SNR) with the advantages of not requiring recognition and extraction of targets, lower computational complexity, and applicability for slow targets, fast targets, and multiple targets of the same range cell. The simulated SAR data and GaoFen-3 SAR data are processed to demonstrate the effectiveness of the proposed method. Furthermore, the radial velocity estimation method is verified by automatic identification system (AIS) information.

Space-time waveform-encoding (STWE) SAR has great potential to improve the performance of the future spaceborne SAR system. With the aim of solving the problem of overlapped echoes, one effective approach involves the use of digital beamforming (DBF) in elevation combined with the null-steering techniques. However, the traditional real-time echo separation scheme with single-null steering techniques occupies huge digital resources. In this letter, a novel real-time echo separation processing scheme in intermediate frequency domain is proposed to overcome the disadvantage of the conventional scheme. Based on the two-dimensional simulation results, the proposed scheme has the same accuracy of separating the overlapped echoes as the traditional scheme. Detailed analysis of the system complexity indicates that the proposed scheme can greatly reduce the resource occupation. Moreover, the effectiveness of the proposed scheme is further verified and demonstrated by the experimental results on the X-band 16-channel DBF-SAR system.

Frequency diverse array synthetic aperture radar (FDA-SAR) has been recognized as a potential technique for high-resolution wide-swath imaging, and employs a slight frequency increment to the transmitting sub-apertures/channels to form a range-dependent beam pattern for swath widening. The key challenge of FDA-SAR is echo separation at the receiver. Former studies have employed quasi-orthogonal waveforms with low cross-correlation energies as the transmitted signals, which can not ensure reliable echo separation, especially for distributed scatterers. In this letter an FDA-SAR processing framework is proposed based on the segmented phase code waveform. An encoding scheme and a notch-expanding receiving beamformer based on convex optimization are used for precise echo separation. Then, using the degrees of freedom on transmitting, a beamformer is applied to resolve range ambiguities. The proposed scheme avoids the performance deterioration caused by the echo separation issue, even for distributed scatterers, while allowing other multiple-channel techniques to be integrated. Simulation experiments have validated the effectiveness of the proposed scheme.

The performance of traditional translational motion compensation methods is degraded when migration through range cell (MTRC) occurs or the echo amplitude is time-varying. In this letter, an effective translational motion compensation approach is proposed for high-resolution inverse synthetic aperture radar (ISAR) imaging with time-varying amplitude. The proposed algorithm based on the minimum mean square error (MMSE) criterion and the energy extraction of prominent point can realize the translational motion compensation accurately. First, the observation time is divided into multiple sub-apertures, and the range alignment of the echoes within each sub-aperture is achieved. Then, the range alignment between sub-apertures is realized based on the MMSE criterion. The Radon transform is performed on the range-aligned echoes to extract the prominent point with the maximum energy, and the envelope fine alignment and phase correction are realized. After rotation compensation, a well-focused ISAR image is obtained. Simulation experiments and real measured data demonstrate the effectiveness of the proposed algorithm.

Synthetic aperture radar (SAR) is an advanced remote sensing technique, capable of observing Earth’s surface independent of weather conditions and sunlight illumination. Restricted by the minimum antenna area, however, conventional spaceborne SAR systems cannot achieve high azimuth resolution in a wide swath. In addition, blind ranges are present as the constant pulse repetition interval (PRI) is used. To solve these problems, a PRI-staggered elevation multichannel SAR (EMC-SAR) system is employed in this article. By transmitting the continuously PRI-varied sequence, the blind ranges are located at different regions in different receive instants, effectively avoiding the loss of coverage in elevation. In this system, three issues are required to be addressed: 1) recovering the missed data located at blind ranges; 2) suppressing range ambiguous components; and 3) restoring the PRI-varied signal into a regular grid. To deal with these problems, we propose a novel SAR imaging method for a PRI-staggered EMC-SAR system. To be applied on-ground, assume downlinking of the individual elevation channels. First, the modified$\varepsilon $-insensitive loss tube regression with the L2 regularization method is applied to recover the missed data. Then, the range ambiguous components are suppressed by performing digital beamforming (DBF) based on the elevation multichannel technique, where the covariance matrix is constructed by using an iterative adaptive algorithm. After that, a generalized scaling transform is employed to restore the PRI-varied signal into a uniform sampled grid. Finally, a well-focused SAR image can be obtained by performing the conventional SAR imaging techniques. The effectiveness of the proposed method is validated by both simulated and real SAR data processing results.

Synthetic aperture radar (SAR), an active remote sensing equipment, shares the spectrum with devices in the same frequency band and is therefore easy to affect by pulse radio frequency interference (PRFI). The wideband version of PRFI, i.e., linear-frequency-modulation PRFI (LFM-PRFI), derived from the ground- and space-based radar sensors is a challenging issue for SAR because it usually has a large bandwidth and pulse width compared with the traditional PRFI. The well-known notch filtering methods, including time- and frequency-domain versions, are robust approaches against PRFI, which has been integrated into some SAR ground processing systems. However, the down-range frequency domain notch filtering will increase the sidelobes of the targets when mitigating wideband LFM-PRFI, whereas the time-domain version will introduce ghosts when notching large pulse-width ones. This paper proposed a filtering method that consists of three steps to tackle the above problems. The first step is focusing the energy of LFM-PRFI down-range and cross-range simultaneously, which can be done by match filtering and Fourier transform. The second step is mitigating the LFM-PRFI, which can be done by a designed filter. The last step is data restoration, which can be done by multiplying the conjugate of the phase function used before. Numerical experiments based on simulated SAR data and measured spaceborne SAR data acquired by European Sentinel-1 are performed to test the mitigation performance, which verified the effectiveness and superiority of the proposed approach.

An important challenge in high-resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is the 2-D spatial-variant (SV) high-order phase error. The classic autofocusing phase correction method cannot effectively correct the SV phase error, which makes it difficult for the traditional range-Doppler (RD) algorithm to obtain high-quality images in high-resolution imaging. The range SV phase error can be compensated for each range cell separately after migration correction of the cross-range cell, but correcting the azimuth SV phase error is challenging. This article presents a high-resolution ISAR imaging algorithm for maneuvering targets with azimuth adaptive partitioning and phase compensation function estimation. First, the coarse-focus image is obtained by the azimuth Fourier transform (FT) after translational motion compensation and migration through range cell (MTRC) correction. Then, the azimuth coarse-focusing result is adaptively partitioned at each range bin. Each partitioned data block is transformed into the time domain, and joint time-frequency analysis (JTFA) is performed to obtain the time-frequency curve of the signal. Through alignment of time-frequency curves, the phase compensation function is inverted. Finally, the corrected subblocks are stitched together to obtain high-quality ISAR images. ISAR imaging experiments with simulated and real data demonstrate the effectiveness and practicability of the proposed algorithm in high-resolution ISAR imaging of maneuvering targets.

Due to the large equivalent transmit crosstalk in hybrid quadrature polarimetric SAR system, traditional calibration methods using azimuthally symmetric distributed targets (AS-Targets) cannot work. In this manuscript, a preprocessing method of AS-Targets' covariance matrix is proposed, which makes equivalent crosstalk after processed become small to achieve system calibration through the AS-Targets. Simulation and airborne SAR data testing verify the reliability of the proposed method. The results show that the method presented in this manuscript can well calibrate the hybrid quadrature polarimetric SAR system using AS-Targets.

By transmitting the constant pulse repetition interval (PRI) sequence, the traditional synthetic aperture radar (SAR) system will suffer from the loss of coverage in elevation. Thus a staggered-SAR system is developed in recent years, which employs the continuously PRI-varied sequence, making the blind ranges locate at different regions in different receive instant. However, the nonuniformly sampled signal will cause ambiguities in the SAR imaging result. To deal with this issue, in this paper, a novel signal restoration method based on kernel regression is proposed to resample the nonuniform signal. Real-measured spaceborne SAR data is used to validate the proposed method.

Next-generation SAR imaging system demands wide-swath and high resolution to observe Earth's surface, promoting the development of the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system working in terrain observation by progressive scans (TOPS). However, Doppler ambiguities will occur in this system, causing the imaging performance severely degrading. To address this issue, in this paper, a novel Doppler ambiguous suppression method for an HRWS-TOPS SAR system based on the orthogonal projection subspace is developed. The effectiveness of the proposed method is verified by both the simulated and real SAR data.

In an azimuth multichannel synthetic aperture radar (SAR) system operating in sliding spotlight mode or Terrain Observation by Progressive Scans (TOPS) mode, due to the varying Doppler centroid and the greater processed Doppler bandwidth, the conventional channel phase error estimation algorithms that tailored to stripmap mode will fail and unable to be directly employed. To address these issues, a deramping-based method is proposed in this letter, which extends the conventional methods to sliding spotlight and TOPS cases. By multiplying the signals of each channel with the corresponding deramp phase, the problem of varying Doppler centroid is solved, and its resulting greater Doppler bandwidth is reduced. Therefore, the spectral properties of the signals are the same as those in the stripmap case, and the conventional channel phase error estimation methods can be applied subsequently. Estimation and imaging results of the simulation data and the real data of GaoFen-3 (GF-3) operating in dual-channel sliding spotlight mode demonstrate the effectiveness of the proposed method.

The spaceborne high-resolution wide-swath synthetic aperture radar (HRWS-SAR) system generally does not meet the optimal SAR imaging configuration, and thus, it is necessary to apply digital beam-forming filtering technology to restore the nonuniformly sampled signal into the uniform grids. However, in practice, because of the influences of temperature, receiving machine, and other error factors, the channel errors may possibly exist, causing the SAR image to be smeared. To address this issue, this letter proposes a novel algorithm based on the hybrid artificial fish school algorithm–glowworm swarm optimization–genetic algorithm (AFSA-GSO-GA) to address the channel imbalance issue. First, coarse HRWS-SAR imaging processing is performed to obtain the positions of the Doppler ambiguity components. Then, according to the designed cost function, the hybrid AFSA-GSO-GA algorithm is used to realize the channel phase error estimation. Finally, a well-focused SAR image can be obtained after channel balance. The effectiveness of the proposed method is validated by both simulated and real SAR data.

The 3-D structure of forests is an important indicator for evaluating forest health and can provide data support for ecological monitoring and protection. Synthetic aperture radar (SAR) tomography (TomoSAR) is an important technology for forest structure estimation using the multibaseline (MB) SAR data stacks. The spectral estimators, such as the Capon method, are usually used to estimate the 3-D reflectivity along elevation direction. In this letter, a modified Capon (M-Capon) method is proposed to improve the estimated profiles of ground and canopy scatterers in the elevation direction, including the estimation accuracy and resolution. This method combines the ideas of the CLEAN algorithm with the Capon method and uses iteration to improve the resolution and accuracy of the estimation. The effectiveness of the M-Capon method is demonstrated using the simulated data and the MB SAR data acquired by the P-band airborne SAR system over the Saihanba Forest Farm in Hebei, China.

Digital beamforming (DBF) is a state-of-the-art technique for high-resolution and wide-swath (HRWS) observation in synthetic aperture radar (SAR) imaging. Since azimuth high-resolution imaging will be a popular tendency in future SARs, DBF-SAR needs to become practical. A new problem arising in airborne DBF-SAR application is the aperture extension loss (AEL). Similar to the pulse extension loss, it is confirmed in our study that AEL will widen the point target responses and degrade the signal-to-noise ratio (SNR) improvement in airborne DBF-SAR. However, little work has been devoted to the compensation of the AEL effect. In this article, the effects of AEL are demonstrated and two compensation methods are proposed, discussed, and implemented for the processing of raw data. The above are demonstrated through simulations and an airborne experimental C-band azimuth high-resolution DBF-SAR. The results show that the AEL compensation removes the AEL effects and increases the SNR with the cost of higher impulse response sidelobes. Moreover, with this novel design scheme, it is demonstrated that azimuth ambiguity suppression can be implemented by elevation DBF.

Currently, in the spaceborne synthetic aperture radar (SAR) community, the sliding spotlight mode has been widely applied to achieve high-resolution imaging. However, limited by the system pulse repetition frequency (PRF), it is usually impossible to realize a large-scale coverage at the same time. The technique of azimuth multichannel alleviates the PRF restriction by receiving additional spatial samples proportional to the number of Rx channels. A system combining the technique of azimuth multichannel with sliding spotlight SAR is able to achieve ultrahigh-resolution and wide-swath imaging simultaneously. In the advanced multichannel sliding spotlight mode, some problems may occur. First, azimuth beam progressive steering leads to an enlarged Doppler bandwidth over$N\cdot \text {PRF}$, and conventional azimuth multichannel reconstruction algorithms developed for the stripmap mode are, thus, not directly suitable for the sliding spotlight mode. Second, the phase characteristics of multichannel sliding spotlight SAR is different from that of multichannel stripmap SAR due to the time variation of the system Doppler centroid. Third, processing of spaceborne multichannel sliding spotlight SAR experimental data shows that the convolution function used in the full-aperture reconstruction method is closely related to the antenna phase configuration strategy of the phased array antenna system. Therefore, an improved processing frame is required for the multichannel sliding spotlight SAR, reexamining the validity of assumptions, such as the stop-go-stop approximation and that of a noncurved trajectory during the relatively long aperture time. Recently, as an exploratory study, a dual-channel sliding spotlight experiment was conducted with the Gaofen-3 (GF-3) SAR. Two experimental data sets were acquired with different PRFs. In this article, the GF-3 payload and the experiment design are introduced, and a complete multichannel sliding spotlight SAR data processing chain is provided. The first imaging results of spaceborne multichannel sliding spotlight SAR are demonstrated.

Multichannel SAR system operating in the sliding spotlight mode has the capacity of imaging with very high resolution as requested by future spaceborne synthetic aperture radar (SAR) mission; hence, it has been attracted more and more attention in the SAR community. In a multichannel sliding spotlight SAR system with$N$channels, the overall Doppler bandwidth of the data acquired by each channel is greater than$N \cdot \text {PRF}$; thus, the preprocessing algorithms (channel mismatch calibration and signal reconstruction) are no more available. To address this issue, a full-aperture imaging method for azimuth multichannel sliding spotlight mode is proposed in this article. First, the raw data of each channel need to be preprocessed based on a deramping operation, which can obtain an unambiguous Doppler spectrum. Afterward, the algorithm proposed for single-channel sliding spotlight mode can be performed. Finally, to avoid possible back-folded SAR images, postprocessing after focusing is demanded in some cases. The imaging results of the data acquired by GaoFen-3 (GF-3) are given for the first time in this article, which proves the effectiveness of the proposed imaging method and demonstrates the capacity of high-resolution wide-swath imaging of the multichannel sliding spotlight mode.

For a spaceborne high-resolution and wide-swath synthetic aperture radar (HRWS-SAR) system, it usually uses the digital beamforming technology. However, in practice, because of the influences of temperature, antenna pattern, receiving antenna, and other error factors, there may exist the range synchronization time errors, amplitude errors, and phase errors among different spatial channels. These nonideal factors will significantly degrade the multichannel data reconstruction performance, resulting in a smeared SAR image. To address this issue, in this article we propose a novel channel error correction algorithm based on the orthogonal projection theory. First, the optimal weight of each Doppler ambiguity component is calculated by the orthogonal projection. Then, the cost function is constructed based on the power maximization criterion, from which the channel phase errors can be obtained. Finally, the HRWS-SAR imaging can be finely realized after performing the channel balancing. Compared with the conventional phase error estimation method, the proposed algorithm does not require to perform the matrix eigenvalue decomposition, avoiding the signal leakage phenomenon under low SNR case. The effectiveness of the proposed algorithm is validated by both airborne and space-borne real SAR data.

The azimuth multichannel spaceborne SAR system can achieve the high-resolution and wide-swath simultaneously. In a high-resolution and wide swath (HRWS) SAR system, the Doppler centroid (DC) frequency estimation is an important step for Doppler ambiguity signal reconstruction, which should be precisely estimated. In this paper, we propose a novel Doppler centroid frequency estimation method for HRWS-SAR system based on modified shuffled frog leafing algorithm (MSFLA). Firstly, the cost function is designed based on the average power difference between ambiguities and useful signal. Then, the MLSFA algorithm is proposed to accomplish the DC estimation. Finally, a good HRWS-SAR image is obtained based on the estimated DC. Compared with the traditional time-domain based DC estimation methods, the proposed method is not affected by the troubled cross-terms induced by high-order moments. The effectiveness of the proposed method is verified by the simulation experiments and real-measured SAR data.

In this letter, a novel method is proposed to estimate the along-track baseline for a multichannel synthetic aperture radar (SAR) system, intended for ground moving target indication (GMTI) applications. First, an adaptive spectrum filtering technique is proposed to compensate the terrain interferometric phase caused by the cross-track baseline and then the ground clutter is rejected by applying the joint-pixel displaced phase center antenna (JPDPCA). After performing the moving target detection, the target radial velocity is estimated according to the azimuth position offset by exploiting the road-aided information. Finally, the along-track baseline is derived based on the subspace projection (SP). The effectiveness of the proposed method is validated by data from the experimental airborne system.

The displaced phase center antennas in azimuth and digital beamforming (DBF) in elevation are two state-of-the-art techniques for achieving high-resolution wide swath (HRWS) imaging in the multichannel synthetic aperture radar (SAR) systems. However, due to the atmospheric turbulence, airborne HRWS-SARs inevitably suffer trajectory disturbances, which will consequently defocus the SAR image. Although various motion compensation (MoCo) methods have been proposed, they are mostly designed for the traditional single-channel SAR and, therefore, ignore the channel-dependent posture error. The posture motion error will introduce residual motion and time-variant channel errors, which not only defocuses the image but also causes azimuth ambiguity and degrades the SNR improvement of the final images of the azimuth multichannel and DBF-SAR, respectively. To solve these problems, a novel MoCo scheme for 2-D multichannel SAR systems is proposed. The posture error is described and calculated in matrix form through the use of quaternions. Then, the posture error is transformed into the translational motion error for each receiving channel and is subsequently compensated precisely. To address the residual aperture-variant motion error, a modified aperture-dependent MoCo is integrated into the proposed scheme. Simulations and airborne experiments, including processing the data of a C-band SAR system with four azimuth channels and an X-band DBF-SAR system with 16 elevation channels, have been implemented to validate the effectiveness of the proposed MoCo scheme.

This paper demonstrates the first experiment of Gaofen-3 (GF-3) satellite operated in dual-channel sliding spotlight mode. First, the raw data of two channels need to be preprocessed, including channel error correction and signal reconstruction, so that it can be focused by the subsequent conventional single-channel sliding spotlight mode imaging methods. After imaging processing, to avoid the possible back-folded SAR image, it is necessary to carry out postprocessing step. The imaging result of the data acquired by GF-3 is first given in this paper, it proves the capacity of achieving high-resolution wide-swath of multi-channel sliding spotlight mode, and the effectiveness of the processing method.

Multichannel in azimuth synthetic aperture radar (SAR) operating in sliding spotlight imaging mode serves as an promising tool to achieve very-high resolution and wide-swath imaging of the earth surface. This paper investigates the aspect of phase mismatch calibration for multichannel sliding spotlight SAR imaging, and an extended azimuth cross correlation method is proposed to deel with the influence of beam rotation in azimuth. Processing with experimental data obtained by a C-band dual-channel sliding spotlight airborne SAR shows the effectiveness of channel phase mismatch cancellation.

A novel imaging algorithm is presented in this paper for focusing the very-high resolution spaceborne synthetic aperture radar (SAR) data of spotlight mode. First, the first step of two-steps processing approach (TSPA) is used to get a high azimuth sampling rate which is higher than PRF for the raw data. Then, the "fast-time" effect of stop-and-go approximation is corrected in 2-D frequency domain. Finally, the back-projection algorithm (BPA) is used to correct the error introduced by the curved orbit and the "slow-time" effect of stop-and-go approximation. The simulation results confirm that the proposed method has good performance. The spaceborne SAR data acquired by Gaofen-3 SAR systems demonstrate the feasibility of the proposed method.

In the multichannel synthetic aperture radar (SAR) systems, unavoidable channel errors will significantly degrade the performance of the ambiguity suppression. To address this problem, a channel phase error estimation method is proposed in this letter. First, the multichannel echo model and the weighted backprojection algorithm are introduced. The channel phase errors are then estimated by maximizing the image intensity using the gradient descent method. The simulation results confirm that the proposed method has higher accuracy and robustness than the orthogonal subspace method. The airborne SAR data acquired by a four-channel strip map C-band airborne SAR system demonstrate the feasibility of the proposed method.

Multi-channel synthetic aperture radar (SAR) in azimuth can overcome the minimum-antenna-area constraint of the conventional SAR in high-resolution and wide-swath (HRWS) imaging. However, the SAR system suffers from amplitude and phase mismatch among channels and nonideal antenna pattern, which will result in azimuth ambiguity and ghost targets in the final image. Therefore, taking the nonbandlimited signal and channel errors into account, a practical azimuth ambiguity-to-signal ratio (AASR) model of multi-channel SAR system is established. Meanwhile, the baseband Doppler centroid (DC) frequency related to channel errors also has an influence on image quality. Then, an effective method is proposed to calculate the baseband DC frequency according to the jumping points of the channel phase errors estimate. Subsequently, considering the effect of azimuth antenna pattern (AAP), a corresponding relationship between the ideal steering vectors and the signal subspace from the decomposing covariance matrix is established. After that, based on the uniqueness of the signal subspace and the correct corresponding relationship, an accurate method is proposed to estimate the channel phase errors by minimizing the minimum mean square error (MMSE) of the signal subspace. Finally, an accurate multi-channel SAR imaging diagram is shown to effectively mitigate the azimuth ambiguous energy caused by channel errors. Simulation and real data experiments, including four channel airborne SAR data with a bandwidth of 210 MHz and the Chinese Gaofen-3 dual receiving channel (DRC) spaceborne SAR data, validate the effectiveness of the proposed calibration method, particularly in low signal-to-noise ratio (SNR).

According to the minimum antenna area constraint, synthetic aperture radar (SAR) systems require a low-pulse repetition frequency (PRF) to image the wide swaths in ocean surface monitoring scenarios. However, the low PRF that is lower than the Doppler bandwidth will cause azimuth ambiguities. This letter proposes a novel method of mitigating azimuth ambiguities when using an undersampled SAR system for ship detection over the open sea. In this letter, the concept of range subspectra is adopted to misregister the azimuth ambiguity signals. In addition, a change detection method that uses a principal component analysis and k-means clustering is adopted to detect differences in the azimuth ambiguities between two range subspectra images in which the azimuth ambiguities are misregistered. By compensating for the ambiguities in the corresponding image, the ambiguities can be mitigated. This method is only appropriate for bright targets over dark backgrounds in which residual energy loss occurs for useful signals. Both simulated and real data processing results have validated the effectiveness of the proposed method and show that it is feasible for maritime surveillance.