Moving Vehicle Wheel Parameter Extraction via Micro-Doppler Feature Based on Matching Pursuit

Yifan Chen, Ning Wang, Lamei Zhang
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引用次数: 1

Abstract

Vehicle recognition using radar echo is critical in many applications. However, the discrimination of different kinds of vehicles is still a difficult problem because of their similar structures. For moving vehicles, besides the conventional features, the micro-Doppler (m-D) features induced by the rotation of vehicle's wheels are also useful in vehicle recognition. Most of current researches related to the m-D effect still analyze only a few scattering points and they are unable to extract the m-D features from the radar echo of the whole scene. Given this problem, in this paper, a moving vehicle wheel parameter extraction method via micro-Doppler feature based on matching pursuit is proposed, which can suppress the irrelevant signal components and extract the m-D features of wheels from the echo signal of the area illuminated by radar. Then the positions and the radiuses of wheels can be extracted for different kinds of vehicles discrimination. The simulations are given to validate the effectiveness of the algorithm and the results show the potential of the proposed method in moving vehicles recognition.
基于匹配追踪的微多普勒特征移动车辆车轮参数提取
利用雷达回波进行车辆识别在许多应用中都是至关重要的。然而,由于车辆结构相似,不同类型车辆的识别仍然是一个难题。对于移动车辆,除了常规特征外,车轮转动引起的微多普勒特征也有助于车辆识别。目前大多数与m-D效应相关的研究仍然只是对少数散射点进行分析,无法从整个场景的雷达回波中提取m-D特征。针对这一问题,本文提出了一种基于匹配追踪的移动车辆车轮参数微多普勒特征提取方法,该方法可以抑制不相关的信号分量,从雷达照射区域的回波信号中提取车轮的m-D特征。然后提取车轮的位置和半径,用于区分不同类型的车辆。仿真结果验证了该算法的有效性,表明了该方法在运动车辆识别中的应用潜力。
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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