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Vibrating Micro-Doppler signature extraction from SAR data using Singular Value Decomposition

机译:使用奇异值分解从SAR数据中提取振动微多普勒签名

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摘要

The effect of target micro-motions on the Synthetic Aperture Radar signal results in micro-Doppler target signatures. These micro-Doppler signatures can be a useful source of information for target classification. However the presence of stationary target and noise in the scene makes the extraction of the micro-Doppler signature a difficult challenge. In this paper a micro-Doppler signature extraction method based on the Singular Value Decomposition is applied to extract the target micro-Doppler features from the received SAR signal. The effectiveness of the proposed approach is confirmed through simulations.
机译:目标微运动对合成孔径雷达信号的影响导致了微多普勒目标信号。这些微多普勒签名可以成为目标分类的有用信息来源。然而,场景中静止目标和噪声的存在使得提取微多普勒信号变得困难。本文采用基于奇异值分解的微多普勒特征提取方法,从接收到的SAR信号中提取目标微多普勒特征。通过仿真证实了该方法的有效性。

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