Cross-Range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture-Extrapolated Sparse Representation

Chen, Hongmeng; Li, Ming; Wang, Zeyu; Lu, Yutong; Cao, Runqing; Zhang, Peng; Zuo, Lei; Wu, Yan

doi:10.1109/lgrs.2017.2710082

Cited by 15 publications

(6 citation statements)

References 13 publications

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“…For the sake of clarity, the relocation results are transformed into the Range-Doppler domain. The detailed DBS imaging method and the DBS stitching method can be found in [59,60]. From Figure 10a, we can see that the potential targets are not relocated on the main lobe of the DBS image after GMTR operation, and the relocated places deviate from the center of the imaging scene.…”

Section: Experimental Results IImentioning

confidence: 99%

Knowledge-Aided Ground Moving Target Relocation for Airborne Dual-Channel Wide-Area Radar by Exploiting the Antenna Pattern Information

Chen¹,

Wang

Gao³

et al. 2021

Remote Sensing

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This paper addresses the problem of ground moving target relocation (GMTR) for airborne dual-channel wide-area radar systems. The monopulse technique can be utilized to perform GMTR. However, in real conditions, the GMTR performance degrades greatly due to the effect of channel mismatch. To tackle this problem, prior knowledge of the antenna pattern information is fully utilized to improve the GMTR performance, and a knowledge-aided GMTR algorithm (KA-GMTR) for airborne dual-channel wide-area radar is proposed in this paper. First, the GMTR model for the two receiving channels is analyzed. The channel mismatch model is constructed, and its expression is derived. Then, the channel mismatch phase error is well estimated by exploiting the prior antenna pattern information based on the least squares (LS) method. Meanwhile, the knowledge-aided monopulse curve (KA-MPC) is derived to perform the direction of arrival (DOA) estimation for potential targets. Finally, KA-GMTR, based on the KA-MPC, is performed to estimate the azimuth offsets and relocate the geometry positions of the potential targets when channel mismatch occurs. Moreover, the target relocation performance is analyzed, and the intrinsic reason that degrades the target relocation accuracy is figured out. The performance assessment based on airborne real-data, also in comparison to the conventional GMTR method, has demonstrated that our proposed KA-GMTR algorithm offers preferable target relocation results under channel mismatch scenarios.

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Section: Experimental Results IImentioning

confidence: 99%

Knowledge-Aided Ground Moving Target Relocation for Airborne Dual-Channel Wide-Area Radar by Exploiting the Antenna Pattern Information

Chen¹,

Wang

Gao³

et al. 2021

Remote Sensing

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“…After range compression and range cell migration correction (RCMC) [41], [42], the received signal becomes…”

Section: ) Range-doppler Spectrum Sequence Generationmentioning

confidence: 99%

Clutter Suppression and Target Tracking by the Low-Rank Representation for Airborne Maritime Surveillance Radar

et al. 2020

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Moving target detection is of vital importance to maritime security and maritime resource protection. However, the detection of slow or weak targets is difficult based on traditional methods. A new detection method is proposed by using the different motion variations of radar moving target and sea clutter in the range-Doppler spectrum sequence. The first step in implementing this method is the separation of moving target and sea clutter by the low-rank representation, in which the target and clutter are modeled as foreground and background components. Subsequently, a sea clutter discriminator is constructed within the sea clutter bandwidth to further remove the sea clutter (false alarms) that exists in the foreground. The proposed method can reduce the sea clutter power while maintaining the target power and improve the detection rate of moving targets, especially slow or weak targets. Data collected with airborne maritime surveillance radar in maritime moving target indication (MMTI) mode are used to validate the performance of the proposed method. The experimental results demonstrate that the improvement in the signal-to-clutter ratio (SCR) obtained with the proposed method is better than that obtained with space-time adaptive processing (STAP, including 1DT-STAP, 3DT-STAP and sparse-STAP) and principal component pursuit (PCP) methods; additionally, the figure of merit (FOM) of the proposed method is higher than that of the constant false alarm rate (CFAR) and PCP method. Furthermore, the tracks of ships are obtained by applying a location constraint to the foreground sequence.

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“…However, for the scene edge targets, the nonuniform sampling model cannot be applied because half-beam width echo data are missed. In another way, the incomplete data can be predicted by data extrapolation method [26], [27], [29], [30]. In [26], the authors propose a knowledge-aided Doppler beam sharpening (DBS) imaging method to extrapolate the azimuthal echo data.…”

Section: Introductionmentioning

confidence: 99%

“…In another way, the incomplete data can be predicted by data extrapolation method [26], [27], [29], [30]. In [26], the authors propose a knowledge-aided Doppler beam sharpening (DBS) imaging method to extrapolate the azimuthal echo data. The method extrapolates the echo data by introducing the autoregressive (AR) model.…”

Section: Introductionmentioning

confidence: 99%

Target Fast Reconstruction of Real Aperture Radar Using Data Extrapolation-Based Parallel Iterative Adaptive Approach

Mao

Zhang

Huo

et al. 2021

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

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Cross-Range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture-Extrapolated Sparse Representation

Cited by 15 publications

References 13 publications

Knowledge-Aided Ground Moving Target Relocation for Airborne Dual-Channel Wide-Area Radar by Exploiting the Antenna Pattern Information

Knowledge-Aided Ground Moving Target Relocation for Airborne Dual-Channel Wide-Area Radar by Exploiting the Antenna Pattern Information

Clutter Suppression and Target Tracking by the Low-Rank Representation for Airborne Maritime Surveillance Radar

Target Fast Reconstruction of Real Aperture Radar Using Data Extrapolation-Based Parallel Iterative Adaptive Approach

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