Wide-swath Synthetic Aperture Radar Research Articles

Suppression of Azimuth Ambiguity for the Detection of Ships on the Ocean by Wide-Swath Synthetic Aperture Radar

Suppression of Azimuth Ambiguity for the Detection of Ships on the Ocean by Wide-Swath Synthetic Aperture Radar

High-Resolution and Wide-Swath SAR Imaging with Space–Time Coding Array

To achieve high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) images, this paper focuses on resolving the problem of separating range-ambiguous echoes with the space–time coding (STC) array. At the modeling stage, the transmit elements and pulses of the STC array are configured with time delay and phase coding modulation, which introduces extra degrees of freedom (DOFs) in the transmit domain. To separate the echoes corresponding to different range-ambiguity regions, the equivalent transmit beamforming is performed in the two-dimensional space–frequency domain. Moreover, in order to compensate for the loss of range resolution during the beamforming progress, the frequency splicing method is proposed. At the analysis stage, the distributed target simulation is provided to demonstrate the effectiveness of obtaining HRWS SAR images in the STC radar. Additionally, the performance of resolving range ambiguity is compared with the traditional radar in terms of the range-ambiguity-to-signal ratio (RASR).

High-Resolution and Wide-Swath SAR Imaging With Sub-Band Frequency Diverse Array

High-resolution and wide-swath imaging serves as an important task for synthetic aperture radar (SAR). However, the tradeoff between high azimuth resolution and wide unambiguous swath coverage has not been well optimized in traditional SAR system. Meanwhile, the ultrawideband signal is required to obtain ultrahigh range resolution imaging. It is not easy to increase the bandwidth directly due to the difficulty of system design. To this end, this article makes notable contribution on a sub-band frequency diverse array framework to realize range ambiguous echoes separation and wideband signal synthesis from narrowband signals. By introducing a small frequency increment across the elements within each subarray, the transmit steering vector within each subarray is range-angle-dependent, making it feasible to resolve range ambiguity in the spatial frequency. In addition, the transmitted waveforms of different subarrays occupy different frequency bands in range frequency domain, which play a pivotal role in achieving high-resolution imaging. With phase compensation and sub-band frequency spectrum splicing technique, the wideband signal can be obtained. Simulation results have verified the effectiveness of the proposed approach.

Ground Moving Target Detection With Nonuniform Subpulse Coding in SAR System

For the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system, the increasing imaging width results in a serious range ambiguity problem, which affects the performance of ground moving target indication (GMTI). In this article, a novel nonuniform subpulse coding (NSPC) scheme is proposed. It is characterized by resorting to range-frequency band resources and detailed coding design for each subpulse, enabling the beam auto-scanning in elevation. Also, the bandpass filtering and digital beamforming (DBF) technology with improved data reconstruction are utilized to realize the separation of subpulses and suppress range ambiguity. The NSPC technique exchanges the signal bandwidth for increasing swath without range ambiguity, and the coded subpulses can be directed to the prescribed regions, while skipping the invalid areas where the echoes are blocked. After that, through the robust principal component analysis (RPCA) method, the moving target detection is performed for each separated region without residual range-ambiguous interference. The proposed approach has been theoretically deduced in detail and the simulation experiments demonstrate its effectiveness.

An Image-Domain Signal Model for Azimuth Multichannel Reconstruction and Its Applications

High-resolution wide-swath (HRWS) synthetic aperture radar (SAR) may benefit from reconstructing signal in image domain, for taking local characteristics of the scene into account. An image-domain signal model for HRWS SAR to reconstruct non-ambiguous image is presented in this paper. This model makes the idea of controlling the regional reconstruction performance and taking the advantage of nonuniform scatter distribution possible. Resolution is also preserved perfectly by the proposed model despite of whatever tradeoff is made between azimuth-ambiguity-to-signal-ratio (AASR) and signal-to-noise-ratio (SNR). The model is derived on back projection (BP) image and can deal with different squint angles and beam steering strategies thanks to BP algorithm. Although the reconstruction is done pixel by pixel, computational burden, which depends on beam steering and the specific constraints in reconstruction, may not severely increase. Two methods for Spotlight SAR and two methods for Stripmap SAR are also presented based on the proposed model to verify the model and demonstrate the potential of it. Simulations on both point target and extended target with different squint angles are carried out to verify the proposed methods, which also verify the proposed model indirectly.

Incidence Angle Normalization of Dual-Polarized Sentinel-1 Backscatter Data on Greenland Ice Sheet

The backscatter coefficients of Synthetic Aperture Radar (SAR) images that observe the Greenland Ice Sheet (GrIS) are incidence angle dependent, which impedes subsequent applications, such as monitoring its surface melting. Therefore, backscatter intensities with varying incidence angles should be normalized. This study proposes an incidence angle normalization method for dual-polarized Sentinel-1 images for GrIS. A multiple linear regression model is trained using the ratio between the backscatter coefficient differences and the incidence angle differences of quasi-simultaneously observed ascending and descending image pairs. Regression factors include the geographical position and elevation. The precision evaluation to the ascending and descending images suggests better normalization results than the widely used cosine-square correction method for horizontal transmit and horizontal receive (HH) images and a slight improvement for horizontal transmit and vertical receive (HV) images. Another dataset of GrIS Sentinel-1 mosaics in four 6-day repeating periods in 2020 is also tested to evaluate the proposed method and yields similar results. For HH images, the proposed method performs better than the cosine-square method, reducing 0.34 dB RMSE on average. The overall accuracy of our proposed method is 0.77 and 0.75 dB for HH and HV images, respectively. The proposed incidence angle normalization method can benefit the application of wide-swath SAR images to the study of large-scale and long-period observation on GrIS.

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

High-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is a promising technique for applications such as maritime surveillance. In the maritime environment, normally only a few targets such as ships are interested. However, before detecting them, considerable receiving resources and computation time are required to receive the echoes of the whole scene and process them to obtain imaging results. This is a heavy burden for online monitoring on platforms with limited resources. To address these issues, different from the concept of whole-scene-oriented imaging, we propose a target-oriented imaging concept, which is implemented by an adaptive receiving–processing–decision feedback framework with feedback connection. (1) To reduce receiving resource consumption, we propose a two-dimensional adaptive receiving module. It receives sub-band echoes of targets only through dechirping and subaperture decomposition in the range and azimuth directions, respectively. (2) To reduce computation time, we propose a target-oriented processing module. It processes subarea echoes of targets only through parallelly conducting inverse fast Fourier transform (IFFT) and back projection (BP) in the range and azimuth directions, respectively. (3) To allocate resources reasonably, we propose a decision module. It decides the necessary receiving window, bandwidth, and image resolution through constant false alarm rate (CFAR) detection. (4) To allocate resources adaptively, we connect three modules with a closed loop to enable feedback. This enables progressive target imaging and detection from rough to fine. Experimental results verify the feasibility of the proposed framework. Compared with the current one, for a typical scenario, at least 30% of the system’s resources and 99% of computation time are saved.

High-Resolution Wide-Swath Ambiguous Synthetic Aperture Radar Modes for Ship Monitoring

This paper proposes two high-resolution, wide-swath synthetic aperture radar (SAR) acquisition modes for ship monitoring that tolerate ambiguities and do not require digital beamforming. Both modes, referred to as the low pulse repetition frequency (PRF) and the staggered (high PRF) ambiguous modes, make use of a wide elevation beam, which can be obtained by phase tapering. The first mode is a conventional stripmap mode with a PRF much lower than the nominal Doppler bandwidth, allowing for the imaging of a large swath, because the ships’ azimuth ambiguities can be recognized as they appear at known positions. The second mode exploits a continuous variation of the pulse repetition interval, with a mean PRF greater than the nominal Doppler bandwidth as the range ambiguities of the ships are smeared and are unlikely to determine false alarms. Both modes are thought to operate in open sea surveillance, monitoring Exclusive Economic Zones or international waters. Examples of implementation of both modes for TerraSAR-X show that ground swaths of 120 km or 240 km can be mapped with 2 m2 resolution, ensuring outstanding detection performance even for small ships. The importance of resolution over noise and ambiguity level was highlighted by a comparison with ScanSAR modes that image comparable swaths with better noise and ambiguity levels but coarser resolutions.

Monitoring the spatial dispersion of an oil slick by enhancing and noise-filtering SAR images using SENTINEL-1 satellite repeat-pass observations

ABSTRACT This article presents a method for monitoring the spatial dispersion of an oil slick and the temporal changes it experiences by enhancing and noise-filtering synthetic aperture radar (SAR) amplitude images. When accidental oil spills occur, spatial dispersion of the initial oil cover and assessing the temporal changes that affect it are important factors for recovery operations. Herein, the method proposed aims to facilitate a better understanding of the potential oil spread and oil-float flow from the source of the spill to adjacent coastal zones. Space-borne wide-swath SAR data is used in this regard, as it covers relatively large areas compared with other ground-based remote-sensing techniques and offer day and night observation under all weather conditions in coastal zones. The backscattered radar signal from a VV polarimetric channel, which showed a higher sensitivity for changes in the sea-surface roughness, was used. Heterogeneous surface-scattering phenomena were observed, and the amplitude image was a prominent factor in the formation of a Bragg surface around the seashore, which facilitated a better understanding of the spatial dispersion of a spilt oil layer and its temporal changes. The proposed method was applied to an oil-slick spread that happened after an oil tanker ran aground on a coral reef near Blue Bay Marine Park, south-east of the Mauritius Island, in July 2020. The method for deriving the separability between the oil and the non-oil sea surface was to render per-pixel classifiers more efficient for both speckle smoothing and texture preservation in satellite images. Furthermore, sea wind speed and direction, derived from SAR amplitude images, were used to assess the limitations and reliability of the proposed method. Based on the results, the proposed method indicated a substantial impact for facilitating a better understanding of the spatial dispersion of oil slicks and the temporal changes that affect them.

Robust Clutter Suppression and Radial Velocity Estimation for High-Resolution Wide-Swath SAR-GMTI

Moving targets are usually smeared and imaged at incorrect positions in synthetic aperture radar (SAR) images due to the target motions during the illumination time. Moreover, a moving target will cause multiple artifacts in the reconstructed image since pulse repetition frequency (PRF) operated in high-resolution wide-swath (HRWS) SAR is very low. In order to reliably indicate moving targets, a robust cancellation algorithm is derived in this paper for clutter suppression in multichannel HRWS SAR, which is free by velocity searching and covariance matrix estimation of clutter plus noise. The proposed multilayer channel-cancellation combined with the deramp processing is designed to sequentially suppress the seriously aliased clutter in HRWS SAR. Experimental results show that the proposed algorithm is efficient and robust in tough situations, and have a superior detection ability in weak targets and low-velocity targets. In addition, the radial velocity estimation algorithm combined with the channel cancellation is exploited to relocate moving targets. The effectiveness of the proposed algorithms is validated by actual spaceborne SAR data acquired by a coordination experiment with two controllable vehicles.

A Transformer-Based Coarse-to-Fine Wide-Swath SAR Image Registration Method under Weak Texture Conditions

As an all-weather and all-day remote sensing image data source, SAR (Synthetic Aperture Radar) images have been widely applied, and their registration accuracy has a direct impact on the downstream task effectiveness. The existing registration algorithms mainly focus on small sub-images, and there is a lack of available accurate matching methods for large-size images. This paper proposes a high-precision, rapid, large-size SAR image dense-matching method. The method mainly includes four steps: down-sampling image pre-registration, sub-image acquisition, dense matching, and the transformation solution. First, the ORB (Oriented FAST and Rotated BRIEF) operator and the GMS (Grid-based Motion Statistics) method are combined to perform rough matching in the semantically rich down-sampled image. In addition, according to the feature point pairs, a group of clustering centers and corresponding images are obtained. Subsequently, a deep learning method based on Transformers is used to register images under weak texture conditions. Finally, the global transformation relationship can be obtained through RANSAC (Random Sample Consensus). Compared with the SOTA algorithm, our method’s correct matching point numbers are increased by more than 2.47 times, and the root mean squared error (RMSE) is reduced by more than 4.16%. The experimental results demonstrate that our proposed method is efficient and accurate, which provides a new idea for SAR image registration.

Channel Phase Calibration for High-Resolution and Wide-Swath SAR Imaging with Doppler Spectrum Sharpness Optimization

Channel phase calibration is a crucial issue in high resolution and wide swath (HRWS) imagery with azimuth multi-channel synthetic aperture radar (SAR) systems. Precise phase calibration is definitely required in reconstructing the full Doppler spectrum for precise HRWS imagery without high-level ambiguities. In this paper, we propose a novel calibration for HRWS SAR imagery by optimizing the reconstructed unambiguous Doppler spectrum. The sharpness of the reconstructed Doppler spectrum is applied as the metric to measure the unambiguity quality, which is maximized to retrieve the element phase error caused by channel imbalance. Real data experiments demonstrate the performance of the proposed calibration for ambiguity suppression in HRWS SAR imagery.

A Novel Time-Domain Frequency Diverse Array HRWS Imaging Scheme for Spotlight SAR

The frequency diverse array (FDA) technique is a novel scheme for high resolution wide swath synthetic aperture radar (SAR) imaging, which employs a frequency increment across the array elements. This introduces a range-angle-dependence to the transmission steering vector, which is exploited for range ambiguity resolution in strip-map SAR. Generally in spotlight mode, scatterers dispersively distributed in azimuth have different Doppler histories, in which the range ambiguity resolution for strip-map SAR fails. To extend the flexibility of FDA, in this paper a novel FDA imaging scheme for spotlight mode SAR is proposed. Exploiting the property of the same illuminated period of all scatterers in spotlight mode, the proposed scheme is carried out entirely in the azimuth time domain, which allows for higher processing efficiency and real-time implementations. Still, excessive Doppler history differences among scatterers deteriorate the scheme performance for azimuth-edge scatterers. Aiming at this situation, a residual angle phase compensation in time domain is considered for the cases of a large azimuth beam width, improving the applicability of the proposed scheme. Compared with existing methods, the proposed spotlight FDA-SAR offers the possibility of achieving simultaneously high azimuth resolution and wide swath performance with high efficiency. Simulations and analyses are performed to demonstrate the effectiveness of the proposed spotlight FDA-SAR scheme.

A High-Precision Motion Errors Compensation Method Based on Sub-Image Reconstruction for HRWS SAR Imaging

High-resolution wide-swath (HRWS) synthetic aperture radar (SAR) plays an important role in remote sensing observation. However, the motion errors caused by the carrier platform’s instability severely degrade the performance of the HRWS SAR imaging. Conventional motion errors compensation methods have two drawbacks, i.e., (1) ignoring the spatial variation of the phase errors of pixels along the range direction of the scene, which leads to lower compensation accuracy, and (2) performing compensation after echo reconstruction, which fails to consider the difference in motion errors between channels, resulting in poor imaging performance in the azimuth direction. In this paper, to overcome these two drawbacks, a high-precision motion errors compensation method based on sub-image reconstruction (SI-MEC) for high-precision HRWS SAR imaging is proposed. The proposed method consists of three steps. Firstly, the motion errors of the platform are estimated by maximizing the intensity of strong points in multiple regions. Secondly, combined with the multichannel geometry, the equivalent phase centers (EPCs) used for sub-images imaging are corrected and the sub-images imaging is performed before reconstruction. Thirdly, the reconstruction is performed by using the sub-images. The proposed method has two advantages, i.e., (1) compensating for the spatially varying phase errors in the range direction, by correcting EPCs, to improve the imaging quality, and (2) compensating for the motion errors of each channel in sub-image imaging before reconstruction, to enhance the imaging quality in the azimuth direction. Moreover, the experimental results are provided to demonstrate that the proposed method outperforms PGA and BP-FMSA.

Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning

Through the Synthetic Aperture Radar (SAR) embarked on the satellites Sentinel-1A and Sentinel-1B of the Copernicus program, a large quantity of observations is routinely acquired over the oceans. A wide range of features from both oceanic (e.g., biological slicks, icebergs, etc.) and meteorologic origin (e.g., rain cells, wind streaks, etc.) are distinguishable on these acquisitions. This paper studies the semantic segmentation of ten metoceanic processes either in the context of a large quantity of image-level groundtruths (i.e., weakly-supervised framework) or of scarce pixel-level groundtruths (i.e., fully-supervised framework). Our main result is that a fully-supervised model outperforms any tested weakly-supervised algorithm. Adding more segmentation examples in the training set would further increase the precision of the predictions. Trained on 20 × 20 km imagettes acquired from the WV acquisition mode of the Sentinel-1 mission, the model is shown to generalize, under some assumptions, to wide-swath SAR data, which further extents its application domain to coastal areas.

Multi-Layer Overlapped Subaperture Algorithm for Extremely-High-Squint High-Resolution Wide-Swath SAR Imaging with Continuously Time-Varying Radar Parameters

Extremely-high-squint (EHS) geometry of the traditional constant-parameter synthetic aperture radar (SAR) induces non-orthogonal wavenumber spectrum and hence the distortion of point spread function (PSF) in focused images. The method invented to overcome this problem is referred to as new-concept parameter-adjusting SAR. It corrects the PSF distortion by adjusting radar parameters, such as carrier frequency and chirp rate, based on instant data acquisition geometry. In this case, the characteristic of signal is quite different from the constant-parameter SAR and therefore, the traditional imaging algorithms cannot be directly applied for parameter-adjusting SAR imaging. However, the existing imaging algorithm for EHS parameter-adjusting SAR suffers from insufficient accuracy if a high-resolution wide-swath (HRWS) performance is required. Thus, this paper proposes a multi-layer overlapped subaperture algorithm (ML-OSA) for EHS HRWS parameter-adjusting SAR imaging with three main contributions: First, a more accurate signal model with time-varying radar parameters in high-squint geometry is derived. Second, phase errors are compensated with much higher accuracy by implementing multiple layers of coarse-to-fine spatially variant filters. Third, the analytical swath limit of the ML-OSA is derived by considering both the residual errors of signal model and phase compensations. The presented approach is validated via both the point- and extended-target computer simulations.

An Unambiguous Imaging Method of Moving Target for Maritime Scenes With Spaceborne High-Resolution and Wide-Swath SAR

In azimuth multichannel high-resolution and wide-swath (AMC-HRWS) synthetic aperture radar (SAR) system, undersampling of azimuth signal results in the failure of the single-channel echo imaging, so the echoes of all the channels should be reconstructed to obtain the unambiguous SAR image. Many methods have been proposed to reconstruct the stationary scene echoes. However, moving targets (MTs) will cause false targets in the reconstructed SAR image, which has a great influence on SAR image interpretation and moving target detection, especially in maritime scenes. Hence, we propose an unambiguous imaging method of the moving target for maritime scenes with AMC-HRWS SAR. First, azimuth deramp processing is introduced to obtain coarse-focused moving targets, and then their echoes can be extracted from the sea clutter. Based on the extracted data, a radial velocity estimation method is proposed, which is high efficiency and does not require redundant channels. In addition, based on the estimated radial velocity and the characteristics of the coarse-focused signal, a novel signal reconstruction method of moving target is presented. The reconstruction performance of this method is not affected by channel imbalance, and false targets can be removed even if there is radial velocity error. Besides, the effectiveness of this scheme is verified by the simulation data and GaoFen-3 SAR real data. The estimated radial velocities of ships are verified by automatic identification system (AIS) information. The imaging results show that false targets are effectively suppressed, and moving targets are located in correct positions.

A Novel Channel Errors Calibration Algorithm for Multichannel High-Resolution and Wide-Swath SAR Imaging

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.

An Effective Clutter Suppression Approach Based on Null-Space Technique for the Space-Borne Multichannel in Azimuth High-Resolution and Wide-Swath SAR System

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

Doppler Centroid Estimation for Ground Moving Target in Multichannel HRWS SAR System

In multichannel high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) ground moving target indication (GMTI) systems, Doppler centroid (DC) is an essential parameter for spectrum reconstruction and image focusing. However, the conventional DC estimator faces many problems in moving target with multichannel SAR system, such as nonuniform data in azimuth, subsignal usage, and channel mismatch. To estimate the DC of moving target, the modified cross-correlation coefficient (MCCC) method for multichannel SAR system is proposed in this letter, which is especially suitable for nonuniform and undersampled data. Simulations with real spaceborne data demonstrate the effectiveness of this method.