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The imaging geometry of the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system.
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Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) compared with conventional SAR. Moving target indication (MTI) is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the proble...
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In synthetic aperture radar (SAR) ocean remote sensing, it is very difficult to estimate an accurate azimuth antenna pattern (AAP) from low-scattering SAR images without strong scattering targets. Therefore, an azimuth antenna pattern estimation method based on Doppler spectrum in SAR ocean images is proposed in this paper. In order to preserve the...
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In synthetic aperture radar (SAR) images, azimuth ambiguity is one of the important factors that affect image quality. Generally, the azimuth ambiguity-to-signal ratio (AASR) is a measure of the azimuth ambiguity of SAR images. For the low signal-to-noise ratio (SNR) ocean areas, it is difficult to accurately estimate the local AASR using tradition...
High-resolution wide-swath (HRWS) synthetic aperture radar (SAR) systems utilize multiple along-track channels to collect additional samples under relatively low pulse repetition frequency (PRF). This manuscript focuses on cross-track velocity estimation of a moving target in HRWS SAR, since this information is an important input parameter to HRWS...
Azimuth multichannel (AMC) synthetic aperture radar (SAR), which contains multiple receiving antennas along the azimuth, can prevent the minimum antenna area constraint and provide high-resolution and wide-swath (HRWS) SAR images. Channel calibration and along-track baseline estimation are important topics in an AMC SAR system, since they have a gr...
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... High-resolution images provide reliable information for the identification, confirmation, and description of maritime targets, especially for small vessels. Wide swath coverage, characterized by high temporal resolution with a short revisit time, allows for capturing and tracking dynamic changes in maritime regions [3,4]. Given that SAR was initially developed for the imaging of stationary scenes, the presence of moving targets within an SAR image will result in both spatial displacement and defocusing due to their motion during the SAR integration time. ...
... Thus, we mainly concentrate on analyzing the influence of moving target imaging in azimuth. According to (3), the signal of the ith moving target in azimuth is simplified as ...
Maritime moving target imaging using synthetic aperture radar (SAR) demands high resolution and wide swath (HRWS). Using the variable pulse repetition interval (PRI), staggered SAR can achieve seamless HRWS imaging. The reconstruction should be performed since the variable PRI causes echo pulse loss and nonuniformly sampled signals in azimuth, both of which result in spectrum aliasing. The existing reconstruction methods are designed for stationary scenes and have achieved impressive results. However, for moving targets, these methods inevitably introduce reconstruction errors. The target motion coupled with non-uniform sampling aggravates the spectral aliasing and degrades the reconstruction performance. This phenomenon becomes more severe, particularly in scenes involving multiple moving targets, since the distinct motion parameter has its unique effect on spectrum aliasing, resulting in the overlapping of various aliasing effects. Consequently, it becomes difficult to reconstruct and separate the echoes of the multiple moving targets with high precision in staggered mode. To this end, motivated by deep learning, this paper proposes a novel Transformer-based algorithm to image multiple moving targets in a staggered SAR system. The reconstruction and the separation of the multiple moving targets are achieved through a proposed network named MosReFormer (Multiple moving target separation and reconstruction Transformer). Adopting a gated single-head Transformer network with convolution-augmented joint self-attention, the proposed MosReFormer network can mitigate the reconstruction errors and separate the signals of multiple moving targets simultaneously. Simulations and experiments on raw data show that the reconstructed and separated results are close to ideal imaging results which are sampled uniformly in azimuth with constant PRI, verifying the feasibility and effectiveness of the proposed algorithm.
... Dedicated methods (Wang, Bi et al., 2017) aim to locate either the ship itself or its wake. Other studies focus on retrieving orientation after detection or on refocusing moving targets (Jin et al., 2017). Integrated detection receives a lot of attention, with Automatic Identification System and SAR being complementary (Zhao et al., 2014). ...
In this review, we present the main approaches developed around satellite and airborne Synthetic Aperture Radar (SAR) imagery. The great range of SAR imagery applications is summarized in this paper. We organize the most popular methods and their applications in a cohesive manner. SAR data applications are classified into earth observation and object detection applications and the former are separated into land, sea, and ice applications. We present the basic methodologies and recent advances in land cover classification and object detection, as well as techniques for parameter retrieval from SAR data. We give advantages and disadvantages and highlight the particular characteristics of each method. It is shown that usage of SAR contributes to the amelioration of techniques and to the enhancement of reliability.
... These methods usually require a long time observation. A modified three-dimensional Capon algorithm based on minimum variance [3] and estimator based on the maximum likelihood [4][5] provide optimum parameter estimation but they cost great calculations to fit the best solution. Radial velocity measurement techniques in modern linear frequency modulation (LFM) radar are mainly based on the Doppler shift measuring by performing one dimension (1-D) fast Fourier transformation (FFT) [6]. ...
In this paper, a new scheme to measure radial velocity based on direction of arrival (DOA) estimation with multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm usual applications in Uniforms Linear Arrays (ULA) don’t enable velocity estimation because the array signals in one snapshot are synchronous and the radial motion does not affect the steering vector. In the proposed scheme, signal snapshot is rearranged so that each vector now contains a sequence of signals from adjacent elements delayed in time, this way the steering vector input to the MUSIC algorithm includes both information of the DOA and radial velocity. An equation describing the relationship of the deviated DOA (dDOA) from the rearranged snapshot with the radial velocity and the DOA is presented. For multi-source situation, pairing problem of DOAs and dDOAs is solved by extracting the combination factors of the steering vectors and the eigenvectors in comparison between the two MUSIC implementations. Comparison with the traditional FFT method shows that a higher accuracy of velocity can be achieved by the proposed method.
... Based on the analysis above, the structure of the Doppler spectrum must be determined accurately before channel error calibration. The idea of eigendecomposition was originally used in array signal processing to determine the direction of arrival of the signal and estimate the gain-phase errors of the system at the time [26]. Furthermore, the eigendecomposition of covariance matrix R( f η ) can be reformulated as follows: ...
... Meanwhile, an M × M diagonal matrix B = diag{b 1 , b 2 , · · · , b M } is defined. The general form of Equation (26) can be written as ...
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.
... High-resolution and wide-swath (HRWS) imaging has become an important trend for the synthetic aperture radar (SAR) technique [1][2][3][4][5], which is conducive to many fields such as continuous earth surface observation [6], moving target indication [7], and maritime reconnaissance [8]. However, for the traditional single-channel SAR system, low pulse repetition frequency (PRF) is required to obtain a wide swath image, which conflicts with the high RPF that is required in azimuth to avoid ambiguity. ...
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.
... However, due to the characteristics of SAR itself, there are still some deficiencies in ship monitoring. First, the Doppler effect between the SAR and target is the key to achieve high azimuth resolution, but the motion of the ship on the sea surface introduces an extra Doppler frequency shift, which results in the azimuth position offset and azimuth defocus of the ship after imaging [5][6][7]. Besides, there are false targets along the azimuth in multichannel mode. All of these damage the quality of the SAR image, which is not conducive to ship surveillance. ...
The synthetic aperture radar (SAR) is an important means of ship surveillance, but the motion of the ship leads to azimuth position offset, false targets, and azimuth defocusing for the spaceborne high-resolution and wide-swath (HRWS) SAR system, causing the degradation of imaging quality. The automatic identification system (AIS) can provide real-time information of the ships, which is an important auxiliary method for ship surveillance. Up to now, the traditional fusion of SAR and AIS mainly has focused on location matching and auxiliary recognition, and the next generation of GaoFen-3 (GF-3NG) satellite is equipped with both a SAR sensor and an AIS sensor to obtain the SAR images and simultaneous AIS information of ships. Consequently, this paper proposes a novel scheme to improve the imaging quality of moving ships for GF-3NG using AIS information. In this paper, through introducing the virtual stationary target, the slant range derivation (SRD) algorithm is proposed to estimate the radial velocity (RV) and the radial acceleration (RA) between the ship and the SAR platform relative to the stationary scene. According to the calculated RV, the azimuth position offset can be estimated and the ship can be repositioned on the image. After that, the traditional method is conducted to suppress the false targets. Finally, the method of using the RA to refocus ship slices is proposed. Additionally, the experiment results based on real data illustrate the effectiveness of the proposed methods.
... In [23], the authors estimated the radial velocity by a group of matched reconstruction filter banks (MRFB), which is also a searching and iteration operation. Besides, in [24], the authors applied the maximum likelihood method to estimate the cone angle as well as the radial velocity. In essence, it is also an iterative process. ...
The azimuth multi-channel synthetic aperture radar (SAR) system can meet the requirements of high resolution and wide swath (HRWS) simultaneously, which overcomes the constraint of the traditional single-channel SAR. However, for a moving target illuminated by the azimuth multi-channel SAR system, its radial velocity will lead to ambiguous components and mislocation in the image. Therefore, the radial velocity estimation plays an important role in improving the image quality and moving target relocation, especially for large ships on the open sea. However, as the pulse repetition frequency (PRF) of a single channel is less than the Doppler spectrum, the traditional velocity estimation methods working in the image domain are out of action. This paper suggests an idea that the issue of velocity estimation is converted into that of the linear phase errors estimation combining the linear fitting method. And it is assumed that the target has been already detected before applying the velocity estimation algorithms. To estimate the linear phase errors, two algorithms operating in the Doppler domain are introduced and compared, namely the subspace-based method (SBM) and the modified frequency correlation method (MFCM). The advantages of the proposed approaches are free from iteration operation and high accuracy. Besides, the effectiveness of the methods is demonstrated via simulation data and GaoFen-3 real data from ultra-fine stripmap (UFS) mode. Finally, the manuscript analyzes the velocity estimation accuracy of the two methods and the influence of channel imbalance through substantial experiments.
... Because there are many sophisticated methods to estimate the imbalance between channels, these techniques will be completed in advance by the data preprocessing process [30][31][32]. In addition, the along-track velocity will only cause the defocus of the target and has no impact on the relocation like the radial velocity [33,34]. Moreover, the unfocused moving target can be well refocused in the image domain by the autofocus technique [35,36]. ...
... And B a = T s · K a is defined as the Doppler bandwidth of the entire scene. N ambi = B a / f r represents the number of the main Doppler spectrum ambiguity [33]. Thus, the relationship between the number of folding times K and the Doppler ambiguity N ambi can be expressed as ...
... And = ⋅ is defined as the Doppler bandwidth of the entire scene. = / represents the number of the main Doppler spectrum ambiguity [33]. Thus, the relationship between the number of folding times and the Doppler ambiguity can be expressed as ...
Azimuth multi-channel Synthetic Aperture Radar (SAR) system operated in burst mode makes high-resolution ultrawide-swath (HRUS) imaging become a reality. This kind of imaging mode has excellent application value for the maritime scenarios requiring wide-area monitoring. This paper suggests a moving target detection (MTD) method of marine scenes based on sparse recovery, which integrates detection, velocity estimation, and relocation. Firstly, the typical phenomenon of scene folding in the coarse-focused domain is introduced in detail. Given that the spatial distribution of moving vessels is highly sparse, the idea of sparse recovery is utilized to acquire the azimuth time characterizing the position of the moving target reasonably. Subsequently, the radial velocity and position information about the targets are obtained simultaneously. What makes the proposed method effective are two characteristics of the moving targets in ocean scenes, high signal-to-clutter ratio (SCR) and sparsity of the spatial distribution. Then, estimation performances under different SCR are analyzed by Monte Carlo experiments. And the actual SCR of the vessels in the ocean scene obtained by GaoFen-3 dual-receive channel mode is invoked as a reference value to verify the effectiveness. Besides, some simulation experiments demonstrate the capability to indicate marine moving targets.
... Modern Earth remote sensing systems have great potential in the fields of mapping and selection of moving targets with their subsequent processing [1][2][3][4][5][6][7][8][9]. In this case, the main tasks of such processing are detection the presence of moving targets and measuring their coordinates and motion parameters [4][5][6][7][8][9][10][11][12][13]. The methods and algorithms for target indication based on the Doppler frequency shift of the echo signal caused by the radial movement of the target are well understood [2][3][4][5][6][7][8][9][10][11][12]. ...
... In this case, the main tasks of such processing are detection the presence of moving targets and measuring their coordinates and motion parameters [4][5][6][7][8][9][10][11][12][13]. The methods and algorithms for target indication based on the Doppler frequency shift of the echo signal caused by the radial movement of the target are well understood [2][3][4][5][6][7][8][9][10][11][12]. At the same time, taking into account the radial component of the velocity allows the selection of only 2/3 of moving ground objects [1,2]. ...
... Let us set the displacement of the apertures equal to m 450 d . Consider the case of a stationary target when 0 t V (figures[10][11]. The magnitude response of stationary point target at the output of the radar signal processing units has the form shown infigure 10 (responses 1). ...
In this paper, the problem of moving target indication (MTI) using synthetic aperture radar (SAR) is considered. The focus of the article is the tangential component of velocity. Two tangential velocity MTI algorithms are considered. The first algorithm uses two apertures with various synthetic time of the radar image (AVST algorithm), and the second uses two apertures displaced along trajectory (ADAT algorithm). The structure of the MTI system based on the analysis of phase and amplitude radar images is considered. For S band and X band SAR, the phase change in the trajectory signal of a moving target, the effects of shift and bifurcation of target responses on the radar image are analyzed in detail. It was found that the AVST algorithm has a small working range of unambiguous velocity estimate (up to ±10 m/s). It is shown that the ADAT algorithm has a higher quality of work in a wide velocity range and can effectively suppress the signals of stationary objects by 20…30 dB. The obtained characteristics allow us to make demands on the parameters of space-borne systems for remote sensing of the Earth and processing systems.
... (Wang et al. 2018) modelled the velocity of the moving target as a phase offset vector and calculated the optimal solution of the cost function, which requires at least one redundant channel. (Jin et al. 2017a) and (Yang, Wang, and Li 2017) estimated the velocity of the moving target based on maximum likelihood (ML) method and sparse direction-of-arrival (DOA) estimation method respectively, however, (Jin et al. 2017a) requires velocity search and (Yang, Wang, and Li 2017) requires angle search. (Jin et al. 2017b) and ) used along-track interferometry (ATI) and equivalent along-track interferometry (EATI) method respectively to obtain the moving target's velocity, but it is difficult to extract the moving target's interferometry phase. ...
... (Wang et al. 2018) modelled the velocity of the moving target as a phase offset vector and calculated the optimal solution of the cost function, which requires at least one redundant channel. (Jin et al. 2017a) and (Yang, Wang, and Li 2017) estimated the velocity of the moving target based on maximum likelihood (ML) method and sparse direction-of-arrival (DOA) estimation method respectively, however, (Jin et al. 2017a) requires velocity search and (Yang, Wang, and Li 2017) requires angle search. (Jin et al. 2017b) and ) used along-track interferometry (ATI) and equivalent along-track interferometry (EATI) method respectively to obtain the moving target's velocity, but it is difficult to extract the moving target's interferometry phase. ...
Multichannel synthetic aperture radar (SAR) is an effective method to achieve high-resolution wide-swath (HRWS) imaging simultaneously. Many algorithms have been proposed to reconstruct stationary targets. However, moving targets cannot be well reconstructed through traditional reconstruct algorithm for static scenes and the ghost targets of the moving targets will have a great influence on SAR image interpretation, especially in maritime scenes. This paper proposed an unambitious imaging method for moving targets in maritime scenes. Firstly, the slant-range velocity of the moving target is estimated through maximizing the minimum variance distortionless response (MVDR) beamformer output in the image domain. Secondly, the phase introduced by the slant-range velocity is compensated before reconstruction. Finally, the Chirp Scaling (CS) algorithm is used to image the full scene and the moving targets can be refocused separately after image formation. The proposed method has the advantage of estimating the slant-range velocity without search or redundant channels. The performance of the proposed method is verified by simulation experiments and real data of Chinese Gaofen-3 (GF-3) SAR sensor.
