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| Ground Moving Target Detection Based on Robust Principal Component Analysis and Shape Constraint |
| GUO Xiaolu TAO Haihong YANG Dong |
| (National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China) |
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Abstract Ground moving target detection is a major application in multichannel Synthetic Aperture Radar (SAR) system. In recent years, method based on Robust Principal Component Analysis (RPCA) has attracted much attention for its good performance in distinguishing the difference among a set of correlative database. However, this kind of method might be disturbed by strong clutter points since some non-ideal factors exist. Therefore, a combined RPCA – shape constraint based algorithm for moving target detection is proposed in this paper. By estimating the shape information of the moving target with system parameters, the moving target would be effectively detected, and the disturbed points would be removed at the same time. The experimental data demonstrate its good performance to detect motive target under the strong clutter background.
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Received: 24 December 2015
Published: 15 July 2016
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| Fund: The National Natural Science Foundation of China (60971108), Xidian University Foundation (BDY061428) |
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Corresponding Authors:
GUO Xiaolu
E-mail: floydguo@foxmail.com
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