Multichannel Synthetic Aperture Radar Research Articles

Robust Reconstruction Method Based on QCQP Optimization for Multichannel SAR With Closely Singular Sampling

The conventional reconstruction algorithm allows for unambiguous recovery of the Doppler spectrum of multichannel synthetic aperture radar (SAR) system in azimuth with an accurately known channel response matrix. However, the available knowledge of the actual channel response matrix is imprecise due to channel errors. In this case, the SAR image will suffer from severe error-induced azimuth ambiguities if reconstructed by the conventional reconstruction algorithm, especially for the case of closely singular sampling. To this end, a novel method based on a quadratically constrained quadratic program (QCQP) optimization is proposed to increase the robustness to the channel errors. Accordingly, the error-induced azimuth ambiguities can be greatly suppressed by the proposed method. Furthermore, performance comparisons of the conventional reconstruction algorithm and the proposed method via numerical simulation are presented.

Scene Adaptive Phase Inconsistency Estimation for Multi-channel ScanSAR System

Operating multi-channel synthetic aperture radar (SAR) in ScanSAR mode enables an ultrawide-swath and high-resolution imagery. A critical step in multi-channel SAR data processing is to accurately estimate and compensate phase inconsistency between channels. However, the Doppler spectrum distribution of ScanSAR relies heavily on the characteristic of illuminated regions, which may make the traditional time-domain phase estimation method failure under nonuniform scenes. In order to ensure that the performance of phase estimation is robust with respect to the variation of scenes, an innovative scene adaptive phase inconsistency estimation method for the ScanSAR system is presented in this letter, which can estimate channel phase error more accurately by extracting scene-center frequency from received data. The performance of the presented approach is evaluated using real airborne multi-channel SAR data. Experimental results show that the modified phase inconsistency estimation method is more effective and adaptable to different scenes compared with the conventional method.

Multichannel SAR Moving Target Detection via RPCA-Net

Ground moving target indication (GMTI), as a challenging task for synthetic aperture radar (SAR) systems, keeps drawing considerable attention. Robust principal component analysis (RPCA) aiming at separating low-rank and sparse components has been successfully employed in SAR systems for GMTI recently. However, its practical application is limited by the heavy computational burden as well as the requirement of manual parameter modification. To cope with this problem, a fast and free of presetting parameters RPCA network (RPCA-Net) is proposed for SAR-GMTI under strong clutter background. In the proposed method, a novel RPCA model is first introduced, where not only the low-rank and sparse terms but also the errors in practical SAR systems are taken into account. Moreover, the low-rank factorization plus scaled gradient descent (ScaledGD) is also employed to acquire low-rank clutter background rather than singular value decomposition (SVD). Then, we parameterize our proposed RPCA model and unfold it as a feedforward neural network (FNN) to acquire the iterative parameters through backpropagation. Compared to the GMTI methods based on traditional RPCA models, our proposed RPCA-Net can provide a higher detection ability and faster convergence without presetting parameters empirically. Experiments on two groups of measured data collected by airborne SAR systems validate the superior performance of the proposed RPCA-Net.

Nonlocal Model-Free Denoising Algorithm for Single- and Multichannel SAR Data

Among the large number of synthetic aperture radar (SAR) image despeckling approaches existing in literature, nonlocal (NL) filters have received a desirable boost. However, often NL approaches define the similarity criterion based on model assumptions, such as a fully developed speckle model. This assumption may not be verified in high-resolution images of urban environments. To address this issue, a standalone model-free despeckling framework is proposed in this article. The presented approach provides a generic framework for denoising a variety of SAR products, from a single-intensity/amplitude image to polarimetric and interferometric SAR data. In particular, the method is based on the empirical distributional similarity between the patch containing the pixel to be recovered and the patch containing a similar candidate pixel. To decide whether the patches follow a similar distribution, the Kolmogorov–Smirnov test is adapted. Finally, the restoration process aggregates the selected similar pixels based on their relative importance derived from their distribution similarities. To mitigate the blurring effect and preserve the resolution, the inhomogeneity of the ratio image is used to perform the bias reduction step. The designed generic despeckling filter was tested on different products of SAR data. The results show that the method proves to be an unbiased restoration approach and is able to preserve structures and textures. It works fully automatically and efficiently with single and multilook (and multichannel) images.

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.

A Two-Stage Echo Separation Scheme for Spaceborne MIMO-HWRS SAR System

Multiple-input and multiple-output synthetic aperture radar (MIMO SAR) is a very potential technique for high-resolution and wide-width (HRWS) imaging due to the fact that it can provide more degrees of freedom. In this paper, an innovative MIMO-HRWS SAR imaging system is introduced with segmented phase coding (SPC) waveforms. However, it is well known that the echo separation issue is the most technical challenge for MIMO SAR. It has shown that the separation of orthogonal echoes from cross-correlation interference can be achieved by scan-on-receive (SCORE). However, this method often requires large computing resources on board, especially for null-steering process. For this, we propose a two-stage spaceborne-ground echo separation scheme. This scheme is mainly divided into two-steps: the first step is a real-time SCORE-beamforming process on board to reduce the downlink data volume, and the second step is a bandpass-null steering process to suppress the interfering echoes on the ground. Thus, this scheme allows for the low computing resources on board and sufficient suppression of the interference simultaneously. Following this scheme, the MIMO-HRWS SAR system enables its number of equivalent phase centers nearly double that of the azimuth multichannel SAR system, thus higher-resolution and wider-swath imaging. Finally, detailed simulation experiments for the MIMO-HRWS SAR imaging system are performed to verify the practicability and feasibility of the proposed scheme.

Distributed Real-Time Image Processing of Formation Flying SAR Based on Embedded GPUs

<b>Formation flying synthetic aperture radar (FF-SAR) systems, as an important development direction of multichannel SAR, can achieve high-resolution wide-swath (HRWS) imaging. Coherently combining data from satellite receivers puts a strain on traditional real-time processing systems based on individual satellites. Characteristics such as the power of real-time on-orbit processing platform must be properly balanced with constrained memory and parallel computational resources. This paper proposes a distributed SAR real-time imaging method based on embedded Graphics Processing Units (GPUs). The parallel computing method of chirp scaling (CS) algorithm is designed based on parallel programming model of compute unified device architecture (CUDA), and the optimization methods of memory and performance are proposed for the hardware architecture of embedded GPUs. In particular, unified memory management method is used to avoid data copying and communication delays between the CPU and GPU. A hardware verification system for distributed SAR real-time imaging processing based on multiple embedded GPUs is constructed. The proposed algorithm takes 5.86 seconds to process single-precision floating-point complex imaging with a data size of 8192 &#x00D7; 8192 on a single Jetson Nano platform. The actual power consumption is less than 5 W, and the performance-to-power ratio is greater than 1.7&#x0025;. The experimental results show that the real-time processing method based on embedded GPUs proposed in this paper has high performance and low power consumption.</b>

Estimating the velocity of moving targets in multichannel SAR images by fourier analysis and optimally-weighted velocity averaging

ABSTRACT A scheme is developed to estimate the radial velocities of moving targets in multichannel synthetic aperture radar (SAR) images. A moving target generally consists of multiple pixels. First, a radial velocity estimate is obtained from each of these pixels via the spatial Fourier analysis, which is more robust against the clutter than the interferometry method because the target signal and the clutter are separate in the spatial frequency domain. Then, the radial velocity estimate of the moving target is obtained by a weighted averaging of the radial velocity estimates, and the weight of each radial velocity estimate is designed to minimize the mean square error (MSE) between the estimate and the truth. This optimally weighted averaging scheme is also more accurate than the optimally weighted averaging scheme related to the interferometry method, because the weight of each radial velocity estimate is designed according to the intensity of the target signal instead of the intensity of the target signal and the clutter. The effectiveness of the proposed scheme is demonstrated by the experimental results of simulated and real SAR data.

An Azimuth Signal-Reconstruction Method Based on Two-Step Projection Technology for Spaceborne Azimuth Multi-Channel High-Resolution and Wide-Swath SAR

Azimuth non-uniform signal-reconstruction is a critical step for azimuth multi-channel high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) data processing. However, the received non-uniform signal has noise in the actual azimuth multi-channel SAR (MCSAR) operation, which leads to the serious reduction in the signal-to-noise ratio (SNR) of the results processed by a traditional reconstruction algorithm. Aiming to address the problem of reducing the SNR of the traditional reconstruction algorithm in the reconstruction of non-uniform signal with noise, a novel signal-reconstruction algorithm based on two-step projection technology (TSPT) for the MCSAR system is proposed in this paper. The key part of the TSPT algorithm consists of a two-step projection. The first projection is to project the given signal into the selected intermediate subspace, spanned by the integer conversion of the compact support kernel function. This process generates a set of sparse equations, which can be solved efficiently by using the sparse equation solver. The second key projection is to project the first projection result into the subspace of the known sampled signal. The secondary projection can be achieved with a digital linear translation invariant (LSI) filter and generate a uniformly spaced signal. As a result, compared with the traditional azimuth MCSAR signal-reconstruction algorithm, the proposed algorithm can improve SNR and reduce the azimuth ambiguity-signal-ratio (AASR). The processing results of simulated data and real raw data verify the effectiveness of the proposed algorithm.

Robust GMTI Scheme for Highly Squinted Hypersonic Vehicle-Borne Multichannel SAR in Dive Mode

While there are recent researches on hypersonic vehicle-borne multichannel synthetic aperture radar in ground moving target indication (HSV-MC-SAR/GMTI), this article, which specifically explores a robust GMTI scheme for the highly squinted HSV-MC-SAR in dive mode, is novel. First, an improved equivalent range model (IERM) for stationary targets and GMTs is explored, which enjoys a concise expression and therefore offers the potential to simplify the GMTI process. Then, based on the proposed model, a robust GMTI scheme is derived in detail, paying particular attention to Doppler ambiguity arising from the high-speed and high-resolution wide-swath. Furthermore, it retrieves the accurate two-dimensional speeds of GMTs and realizes the satisfactory performance of clutter rejection and GMT imaging, generating the matched beamforming and enhancing the GMT energy. Finally, it applies the inverse projection to revise the geometry shift induced by the vertical speed. Simulation examples are used to verify the proposed GMTI scheme.

Hybrid Analog-Digital SAR Instrument With Reflector Antenna and Overlapped Subarray Feed for Earth Observation

As part of the European Space Agency (ESA) studies of new instrument for Earth observation, the design of a synthetic aperture radar (SAR) architecture based on overlapped array antennas was launched last year. The objective of the activity is to develop a test unit of a reflector based SAR antenna fed by an array organized in overlapped subarrays, supporting novel multichannel wide-swath SAR architectures, and exploiting multiple beams in both azimuth and range/elevation directions. In the letter, a hybrid analog/digital beamforming on reception with analog beamforming approach on transmission is analyzed. The antenna system consists of a large oversize reflector with a feedarray capable of generating multiple beams on receive for digital processing. In the letter, a description of the hybrid SAR Instrument is presented, describing the characteristics of the system, the antenna, the considered feedarray options and the main characteristics and system performances.

New Channel Errors Estimation Method for Multichannel SAR Based on Virtual Calibration Source

The multichannel synthetic aperture radar (SAR) system can effectively overcome the fundamental limitation between high-resolution and wide-swath. However, the unavoidable channel errors will result in a mismatch of the reconstruction filter and false targets in pairs. To address this issue, a novel channel errors calibration method is proposed based on the idea of minimizing the mean square error (MMSE) between the signal subspace and the space spanned by the practical steering vectors. The practical steering matrix of each Doppler bin can be constructed according to the Doppler spectrum. Compared with the time-domain correlation method, the proposed method no longer depends on the accuracy of the Doppler centroid estimation. Besides, compared with the orthogonal subspace method, the proposed method has the advantage of robustness under the condition of large samples by using the diagonal loading technique. To evaluate the performance, the results of simulation data and the real data acquired by the GF-3 dual-channel SAR system demonstrate that the proposed method has higher accuracy and more robustness than the conventional methods, especially in the case of low SNRs and high non-uniformity.

Motion Phase Compensation Methods for Azimuth Ambiguity Suppression in HRWS SAR

The azimuth multi-channel synthetic aperture radar (SAR) is widely used in marine observation, because of its excellent imaging ability of high-resolution and wide-swath (HRWS) signals. Different from the static targets, the azimuth ambiguity of the ships on the open sea resulting from the radial motion seriously affects the SAR image quality and ship detection probability. As a result, two methods of azimuth ambiguity suppression for moving ships based on motion phase compensation are proposed to apply to different practical application conditions. The simulation and real measured data experiments verify the ability of image quality improvement by proposed methods.

A two-step channel mismatch estimation and compensation method for distributed MC SAR

ABSTRACT A distributed multichannel synthetic aperture radar system refers to a multichannel synthetic aperture radar system with channels distributed and installed at different locations on the platform. It is a promising system for high-resolution wide-swath imaging. The channels of the distributed multichannel synthetic aperture radar are sparsely distributed and have long cross-track baselines. The range-variant envelope migration and phase mismatch in the echoes between different channels are introduced by the long cross-track baselines and affect the performance of azimuth signal reconstruction. The sparsity of channels results in the poor correlation of data between channels, so the time-domain cross-correlation method typically used in azimuth multichannel synthetic aperture radar cannot be used in distributed multichannel synthetic aperture radar to estimate channel phase error directly. In this paper, the gain-phase error, sampling time delay and slant range difference introduced by cross-track baselines are modelled uniformly as channel mismatches. Firstly, a two-step channel mismatch estimation and compensation method for distributed multichannel synthetic aperture radar is proposed. Secondly, a range-variant envelope migration compensation method based on the chirp scaling principle is given. Thirdly, this paper also presents the processing of data rearrangement based on the distribution of spatial sampling points to make the time-domain cross-correlation method suitable for distributed multichannel synthetic aperture radar. Point target simulation and scene simulation are provided to show the effectiveness of the proposed methods.

A Novel Sub-Image Local Area Minimum Entropy Reconstruction Method for HRWS SAR Adaptive Unambiguous Imaging

Multichannel high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is a vital technique for modern remote sensing. As multichannel SAR systems usually face the problem of azimuth nonuniform sampling resulting in azimuth ambiguity, the conventional reconstruction methods are adopted to obtain the uniformly sampled signal. However, various errors, especially amplitude, phase, and baseline errors, always significantly degrade the performance of the reconstruction methods. To solve this problem, in this paper, a novel sub-image local area minimum entropy reconstruction method (SILAMER) is proposed, which has favorable adaptability to the HRWS SAR system with various errors. First, according to the idea of image domain reconstruction, the sub-images are generated by employing the back-projection algorithm. Then, we proposed an estimation algorithm based on sub-image local area minimum entropy to obtain the optimal reconstruction coefficient and the compensation phase, which can greatly improve the estimation efficiency by using a local area of the sub-image as the input for estimation. Finally, the sub-images are weighted by the optimal estimated reconstruction coefficient and calibrated by the compensation phase to obtain the unambiguous reconstruction image. The experimental results verify the effectiveness of the proposed method. Noticeably, the proposed algorithm has two additional advantages, i.e., (1) it can perform well under the condition of low signal-to-noise ratio (SNR), and (2) it is suitable for the curved trajectory SAR reconstruction. The simulations verify these advantages of the proposed method.

A Study on the Range Equation Modeling for Multichannel Medium-Earth-Orbit SAR-GMTI Systems

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

Estimating ground moving-target parameters for hybrid baseline multi-channel SAR based on migration features in the complex image domain

ABSTRACT The hybrid baseline Multi-Channel Synthetic Aperture Radar (MC-SAR) refers to a MC-SAR with both along-track baselines and cross-track baselines. In the hybrid baseline MC-SAR, the phase induced by the target motion couples with the phase induced by terrain, which leads to the difficulty of ground moving target parameters estimation. In this paper, A novel maximum likelihood method based on the migration feature of a moving target in the complex image domain is proposed to estimate the velocity and height of the moving target. Compared with the original maximum likelihood method, the proposed method can decrease the computational load, has a smaller estimated error, and could resolve the ambiguity. The signal model of the terrain clutter and moving target in the hybrid baseline is analysed. A nonlinear antenna configuration is used to decouple the phase induced by moving target and terrain. Finally, some numerical experiments and scene simulation are also provided to demonstrate the estimated performance with different system parameters and the effectiveness of the proposed method.

A novel hypersonic vehicle-borne multichannel SAR-GMTI scheme based on adaptive sum and difference beams within eigenspace

This paper investigates a novel ground moving target indication (GMTI) scheme for a hypersonic vehicle-borne multichannel synthetic aperture radar (MC-SAR) system with Doppler ambiguity. First, after the range compression and azimuth chirp Fourier transform (CFT), by applying the eigenspace-based adaptive sum and difference beams (EASDB) on the coarse-focused images, the high-precision cross-track velocity (CTV) can be retrieved. Then, utilizing the high-precision CTV to construct an accurate moving target steering vector to extract the moving target energy. With the proposed CFT-two-step method, we have avoided cumbersome CTV search, and simplified the process of range walk correction, resulting in lower computational complexity. Compared to the CFT-center and CFT-two-step methods, the proposed scheme obtains the accurate two-dimension motion parameters of a moving target, and has better performance and robustness in the detection, focusing, and location, preserving the moving target envelope and achieving higher signal-to-clutter-and-noise ratio (SCNR). Finally, using the processing results of simulation and real measured MC-SAR data, we verify the effectiveness and feasibility of our proposed scheme.

Robust Clutter Suppression and Ground Moving Target Imaging Method for a Multichannel SAR with High-Squint Angle Mounted on Hypersonic Vehicle

This paper investigates a robust clutter suppression and detection of ground moving target (GMT) imaging method for a multichannel synthetic aperture radar (MC-SAR) with high-squint angle mounted on hypersonic vehicle (HSV). A modified coarse-focused method with cubic chirp Fourier transform (CFT) is explored first that permits the coarsely focused imageries to be recovered, thus alleviated the impacts of GMT Doppler ambiguity and range cell migration (RCM). After that, in combination with joint-pixel model, a robust clutter suppression method which enhances the GMT integration, and improving the accuracy of radial speed (RS) recovery by modifying the matching between the beamformer center and GMT, is proposed. Due to that the first-order phase compensation and RS retrieval are predigested, the proposed algorithm has lower the algorithmic complexity. Finally, the feasibility of our proposed method are verified via experimental results based on simulated and real measured data.

High-Speed Lightweight Ship Detection Algorithm Based on YOLO-V4 for Three-Channels RGB SAR Image

Synthetic Aperture Radar (SAR) has become one of the important technical means of marine monitoring in the field of remote sensing due to its all-day, all-weather advantage. National territorial waters to achieve ship monitoring is conducive to national maritime law enforcement, implementation of maritime traffic control, and maintenance of national maritime security, so ship detection has been a hot spot and focus of research. After the development from traditional detection methods to deep learning combined methods, most of the research always based on the evolving Graphics Processing Unit (GPU) computing power to propose more complex and computationally intensive strategies, while in the process of transplanting optical image detection ignored the low signal-to-noise ratio, low resolution, single-channel and other characteristics brought by the SAR image imaging principle. Constantly pursuing detection accuracy while ignoring the detection speed and the ultimate application of the algorithm, almost all algorithms rely on powerful clustered desktop GPUs, which cannot be implemented on the frontline of marine monitoring to cope with the changing realities. To address these issues, this paper proposes a multi-channel fusion SAR image processing method that makes full use of image information and the network’s ability to extract features; it is also based on the latest You Only Look Once version 4 (YOLO-V4) deep learning framework for modeling architecture and training models. The YOLO-V4-light network was tailored for real-time and implementation, significantly reducing the model size, detection time, number of computational parameters, and memory consumption, and refining the network for three-channel images to compensate for the loss of accuracy due to light-weighting. The test experiments were completed entirely on a portable computer and achieved an Average Precision (AP) of 90.37% on the SAR Ship Detection Dataset (SSDD), simplifying the model while ensuring a lead over most existing methods. The YOLO-V4-lightship detection algorithm proposed in this paper has great practical application in maritime safety monitoring and emergency rescue.