微多普勒信号的经验模态分解

C. Cai, Weixian Liu, J. Fu, Lilong Lu
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引用次数: 51

摘要

由雷达目标结构的机械振动或旋转引起的微多普勒对目标的探测、分类和识别具有潜在的应用价值。为了利用时变微多普勒信号,采用时频分析技术。然而,它们并不能始终清楚地表示这些有用的信息。本文介绍了一种利用经验模态分解技术提取微多普勒信号的新算法。仿真和实验结果都表明,EMD为微多普勒信号的时频表征提供了一种有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empirical mode decomposition of micro-Doppler signature
Micro-Doppler induced by mechanical vibration or rotation of structures in a radar target is potentially useful for target detection, classification and recognition. In order to exploit the time-varying micro-Doppler signature, time frequency analysis techniques are used. However, they can not represent this useful information clearly all the time. In this paper, we introduce a novel algorithm to extract the micro-Doppler signature using a technique called empirical mode decomposition. Both simulation and the experimental results indicate that EMD provides us an effective way to give better time frequency representation of the micro-Doppler signature.
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