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高分三号双通道SAR/GMTI强杂波抑制研究

Research on Strong Clutter Suppression for Gaofen-3 Dual-Channel SAR/GMTI.

作者信息

Zheng Mingjie, Yan He, Zhang Lei, Yu Weidong, Deng Yunkai, Wang Robert

机构信息

Space Microwave Remote Sensing System Department, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China.

Institute of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210006, China.

出版信息

Sensors (Basel). 2018 Mar 26;18(4):978. doi: 10.3390/s18040978.

DOI:10.3390/s18040978
PMID:29587437
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5948709/
Abstract

In spaceborne synthetic aperture radar (SAR), moving targets are almost buried in ground clutter due to the wide clutter Doppler spectrum and the restricted pulse repetition frequency (PRF), which increases the difficulty of moving target detection. Clutter suppression is one of the key issues in the spaceborne SAR moving target indicator operation. In this paper, we describe the clutter suppression principle and analyze the influence of amplitude and phase error on clutter suppression. In the following, a novel dual-channel SAR clutter suppression algorithm is proposed, which is suitable for the Gaofen-3(GF-3) SAR sensor. The proposed algorithm consists of three technique steps, namely adaptive two-dimensional (2D) channel calibration, refined amplitude error correction and refined phase error correction. After channel error is corrected by these procedures, the clutter component, especially a strong clutter component, can be well suppressed. The validity of the proposed algorithm is verified by GF-3 SAR real data which demonstrates the ground moving-target indication (GMTI) capability of GF-3 SAR sensor.

摘要

在星载合成孔径雷达(SAR)中,由于杂波多普勒频谱较宽且脉冲重复频率(PRF)受限,运动目标几乎被掩埋在地面杂波中,这增加了运动目标检测的难度。杂波抑制是星载SAR动目标显示操作中的关键问题之一。在本文中,我们描述了杂波抑制原理,并分析了幅度和相位误差对杂波抑制的影响。接下来,提出了一种适用于高分三号(GF-3)SAR传感器的新型双通道SAR杂波抑制算法。该算法包括三个技术步骤,即自适应二维(2D)通道校准、精细幅度误差校正和精细相位误差校正。通过这些步骤校正通道误差后,杂波分量,尤其是强杂波分量,可以得到很好的抑制。通过GF-3 SAR实际数据验证了所提算法的有效性,该数据展示了GF-3 SAR传感器的地面动目标指示(GMTI)能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/2f7df8537e94/sensors-18-00978-g017.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/ba86e5abb629/sensors-18-00978-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/73ed5e4a34c5/sensors-18-00978-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/2f7df8537e94/sensors-18-00978-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/1dd2289ee5c7/sensors-18-00978-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/fad2afcf75bd/sensors-18-00978-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/73bfaa885cb7/sensors-18-00978-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/347bf480849b/sensors-18-00978-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/3782d59a9b68/sensors-18-00978-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/ade2a35b940e/sensors-18-00978-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/95a5858fda85/sensors-18-00978-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/4f27f9265f10/sensors-18-00978-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/3252d5fd0920/sensors-18-00978-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/00d668a74015/sensors-18-00978-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/7caa96c376e4/sensors-18-00978-g011a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/d74d8d8ad9e8/sensors-18-00978-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/a1cad1139029/sensors-18-00978-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/6fa1be839706/sensors-18-00978-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/ba86e5abb629/sensors-18-00978-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/73ed5e4a34c5/sensors-18-00978-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f27/5948709/2f7df8537e94/sensors-18-00978-g017.jpg

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本文引用的文献

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Sensors (Basel). 2017 Oct 23;17(10):2419. doi: 10.3390/s17102419.
3
Unambiguous Imaging of Static Scenes and Moving Targets with the First Chinese Dual-Channel Spaceborne SAR Sensor.
利用首个中国双通道星载合成孔径雷达传感器对静态场景和移动目标进行清晰成像。
Sensors (Basel). 2017 Jul 25;17(8):1709. doi: 10.3390/s17081709.
4
Fast Vessel Detection in Gaofen-3 SAR Images with Ultrafine Strip-Map Mode.基于高分三号超精细条带模式SAR图像的快速舰船检测
Sensors (Basel). 2017 Jul 5;17(7):1578. doi: 10.3390/s17071578.
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Signal subspace fusion of uncalibrated sensors with application in SAR and diagnostic medicine.未校准传感器的信号子空间融合及其在合成孔径雷达和诊断医学中的应用。
IEEE Trans Image Process. 1999;8(1):127-37. doi: 10.1109/83.736707.