An EMD-Based Micro-Doppler Signature for Moving Vehicles Classification

Shuangyan Zhai, Tong Mao, Bing Hu
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引用次数: 3

Abstract

It is vital to discriminate wheeled vehicles and tracked vehicles because of their different role on modern battlefields. Micro-Doppler induced by mechanical vibration or rotation of structures in a radar target is potentially useful for target detection, classification and recognition. In this paper, a feature extraction of micro-Doppler information of vehicle is proposed. Then the signal is decomposed by empirical mode decomposition (EMD), and effective features would be extracted. At last, the SVM classifier is used to classify the moving vehicles.
基于emd的移动车辆分类微多普勒特征
轮式车辆与履带式车辆在现代战场上扮演着不同的角色,因此区分轮式车辆与履带式车辆至关重要。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。本文提出了一种车辆微多普勒信息的特征提取方法。然后对信号进行经验模态分解(EMD),提取有效特征。最后,利用支持向量机分类器对运动车辆进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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