Status and Prospects of Radar Polarimetry Techniques
Wang Xuesong
(National University of Defense Technology, Changsha 410073, China)
Abstract Radar polarimetry is an applied fundamental science field that is focused on understanding interaction processes between radar waves and targets and disclosing their mechanisms. Radar polarimetry has significant application prospects in the fields of microwave remote sensing, earth observation, meteorological measurement, battlefield reconnaissance, anti-interference, target recognition, and so on. This study briefly reviews the development history of radar polarization theory and technology. Next, the state of the art of several key technologies within radar polarimetry, including the precise acquisition of radar polarization information, polarization-sensitive array signal processing, target polarization characteristics, polarization antiinterference, and target polarization classification and recognition, is summarized. Finally, the future developments of radar polarization technology are considered.
Key words : Polarimetric radar
Radar imaging
Polarization precise measurement
Polarimetric calibration
Polarimetric filter
Target recognition
Anti-interference
Received: 2016-02-16;
Published: 2016-04-25
Fund: The National Natural Science Foundation of China (61490690, 61490693, 61302143)
Cite this article:
. Status and Prospects of Radar Polarimetry Techniques[J]. JOURNAL OF RADARS, 2016, 5(2): 119-131.
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Wen Gongjian, Zhu Guoqiang, Yin Hongcheng, Xing Mengdao, Yang Hu, Ma Conghui, Yan Hua, Ding Baiyuan, Zhong Jinrong. SAR ATR Based on 3D Parametric Electromagnetic Scattering Model [J]. JOURNAL OF RADARS, 2017, 6(2): 115-135.
[4]
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[9]
Tian Zhuangzhuang, Zhan Ronghui, Hu Jiemin, Zhang Jun. SAR ATR Based on Convolutional Neural Network [J]. JOURNAL OF RADARS, 2016, 5(3): 320-325.
[10]
Dai Da-hai, Liao Bin, Xiao Shun-ping, Wang Xue-song. Advancements on Radar Polarization Information Acquisition and Processing [J]. JOURNAL OF RADARS, 2016, 5(2): 143-155.
[11]
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