Joint Detection of Moving Target in Video Synthetic Aperture Radar

被引:0
作者
Ding J. [1 ]
Zhong C. [1 ]
Wen L. [1 ]
Xu Z. [1 ]
机构
[1] National Laboratory of Radar Signal Processing, Xidian University, Xi’an
基金
中国国家自然科学基金;
关键词
Moving target detection; Radar imaging; Shadow detection; Video radar; Video SAR;
D O I
10.12000/JR22036
中图分类号
TN95 [雷达];
学科分类号
080904 ; 0810 ; 081001 ; 081002 ; 081105 ; 0825 ;
摘要
Video Synthetic Aperture Radar (SAR) presents great potential in ground moving target detection and tracking through high frame rate and high-resolution imaging. Target Doppler energy is essential for traditional SAR Ground Moving Target Indication (SAR-GMTI), as the target shadow can also be used for detection in video SAR. However, neither of these detection methods can stand alone to achieve robust detection in video SAR, owing to the distortion or smearing of target energy and its shadow. This paper presents the processing results of airborne video SAR real data using the Faster Region-based Convolutional Neural Network (Faster R-CNN) and the traditional track association based on dual-domain joint detection as proposed in the literature. These two approaches successfully utilize the feature and space time information of target Doppler energy and shadow in the detection of a maneuvering target. © 2022 Institute of Electronics Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码:313 / 323
页数:10
相关论文
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