A Method of Marine Moving Targets Detection in Multi-Channel ScanSAR System

Yang, Junying; Qiu, Xiaolan; Shang, Mingyang; Zhong, Lihua; Ding, Chibiao

doi:10.3390/rs12223792

Cited by 7 publications

(12 citation statements)

References 41 publications

(53 reference statements)

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“…Because the linear phase errors between channels mean that the strong point being analyzed is equivalent to a moving target rather than a stationary one. From [14], although the moving target focuses on the same position as the stationary in the coarse-focused domain, its motion will make its real position deviate from the stationary target. The linear components in the phase mismatch can be expressed as Then, the quantitative relationship between the linear phase and the position deviation Δ is derived as…”

Section: Influence Of Phase Imbalance On Results Of Sparse Recoverymentioning

confidence: 99%

“…This section begins with a brief review of the theoretical description of multi-channel SAR in Scan operation shown as Fig. 1 [11] [14]. It transmits pulses by the reference channel with low PRF and receives the pulses with N sub-apertures in the along-track direction at the same time.…”

Section: Multi-channel Scan Operationmentioning

confidence: 99%

“…For the echo of a burst in the azimuth multi-channel ScanSAR system, the time length corresponding to the whole imaging area is + [14] and the interval is / . Consequently, the number of scene ambiguity is calculated as…”

Section: A Scene Ambiguitymentioning

confidence: 99%

“…Thus, the azimuth multi-channel system could sample the signal with a large Doppler bandwidth with a sufficiently high PRF, which corresponds to the high resolution [13]. In addition, to obtain an ultrawide swath, the azimuth multi-channel ScanSAR system switches the antenna footprint between several sub-swathes [14]. The operating principle implies that the PRF of a single channel will be less than the Doppler bandwidth of the system.…”

Section: Introductionmentioning

confidence: 99%

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Phase Imbalance Estimation for Azimuth Multi-Channel ScanSAR System

Yang

Qiu

Shang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The new concept of combining the azimuth multichannel synthetic aperture radar (SAR) system with the Scan mode was put forward to meet the requirements of future developments in high-resolution and ultrawide-swath (HRUS) SAR design. However, the phase imbalance between channels is inevitable, which will greatly reduce the quality of the image. This paper proposed an approach of phase imbalance estimation for azimuth multi-channel ScanSAR system. For this, the particularity of the target Doppler spectrum in Scan mode is analyzed firstly. Then, the theoretical derivation reveals the equivalence of scene ambiguity and Doppler spectrum ambiguity. Subsequently, the main idea of the proposed approach is to determine the index of the ambiguous component of the target in the Doppler spectrum by the sparse recovery method. The equivalent multi-channel ScanSAR real measured data experiment demonstrates the effectiveness of the proposed approach. Compared with the estimation results of the signal subspace comparison method (SSCM), the proposed method shows better performance. Finally, the details in the implementation process of the proposed algorithm are described by combining theoretical analysis with simulation experiments.

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Section: Influence Of Phase Imbalance On Results Of Sparse Recoverymentioning

confidence: 99%

Section: Multi-channel Scan Operationmentioning

confidence: 99%

Section: A Scene Ambiguitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Phase Imbalance Estimation for Azimuth Multi-Channel ScanSAR System

Yang

Qiu

Shang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Target motion introduces variations in both Doppler spectrum and range cell migration (RCM) [5][6][7], which will result in target position shift and resolution distortion in SAR image. Moreover, the effect on SAR image is different in side-looking and azimuth squintlooking.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Renewable Energy Resources with Remote Sensing

Martins¹

2021

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Imaging position shift based on the multiple azimuth squint angles (MASA) mode is effective for target azimuth velocity estimation, whereas accuracy is low when target range velocity is high. In this paper, the estimation problem for both target azimuth and range velocities is considered based on the multi-channels MASA (MC-MASA) mode. Firstly, the acquisition geometry of MC-MASA mode and Doppler characteristics of a moving target are analyzed in detail, especially in squint mode. Then, for better moving target estimation, the stationary background clutter is removed using the displacement phase center antenna (DPCA) technique, and the failure in range velocity estimation with sequential SAR images is also discussed. Furthermore, a modified alongtrack interferometry (ATI) is proposed to preliminarily reconstruct the azimuth-and-range velocity map based on the MC-MASA mode. Since the velocity estimation accuracy is dependent on squint angle and signal-to-clutter ratio (SCR), the circumstances are divided into three cases with different iteration estimation strategies, which could expand the scene application scope of velocity estimation and achieve a high estimation accuracy along both azimuth and range directions. Finally, the performance of the proposed method is demonstrated by experimental results.

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Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

Wen

Wei

2022

Entropy

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In marine radar target detection, sea clutter will cause a large number of missed alarms and false alarms, which will affect the accuracy of target detection. In order to suppress sea clutter effectively, a sea clutter suppression and target detection algorithm of marine radar image sequence based on spatio-temporal domain joint filtering is proposed in this paper. The proposed method is to add a sea clutter suppression link before detecting the target. Firstly, the marine radar image sequence is transformed into three-dimensional frequency wavenumber domain by three-dimensional fast Fourier transform (3D-FFT), and then the three-dimensional image spectrum is obtained. According to the fact that the sea clutter spectrum obtained from the image spectrum satisfies the dispersion relation of linear wave theory in the three-dimensional frequency wavenumber domain, a sea clutter model is established. Then, through the established sea clutter model, a spatio-temporal domain joint sea clutter suppressor is designed to filter the image spectrum. After that, the filtered image spectrum is transformed by three-dimensional inverse fast Fourier transform (3D-IFFT) to obtain the image sequence in which sea clutter is suppressed. Finally, target detection is carried out for sea clutter suppressed image sequence. The method is validated by using the real data of X-band marine radar. Compared with the classical Empirical mode decomposition (EMD) method, the improvement of signal-to-noise ratio (SNR) is more obvious, and SNR can be increased by 15.3 db at most. In addition, compared with target detection on original images directly, the proposed method has excellent detection rate and can increase detection rates by at least 8%.

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A Method of Marine Moving Targets Detection in Multi-Channel ScanSAR System

Cited by 7 publications

References 41 publications

Phase Imbalance Estimation for Azimuth Multi-Channel ScanSAR System

Phase Imbalance Estimation for Azimuth Multi-Channel ScanSAR System

Assessment of Renewable Energy Resources with Remote Sensing

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

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