A neural network approach to target classification for active safety system using microwave radar

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摘要

As a sensor in the active safety system of vehicles, the microwave radar (MWR) would be a good choice for the localization of the nearby targets but could be a bad choice for their classification or identification. In this paper, a target classification system using a 24 GHz microwave radar sensor is proposed for the active safety system. The basic idea of this paper is that the pedestrians and the vehicles have different reflection characteristics for a microwave. A multilayer perceptron (MLP) neural network is employed to classify the targets and the probabilistic fusion is conduct over time to improve the classification accuracy. Some experiments are performed to show the validity of the proposed system.

论文关键词:Target classification,Multilayer perceptron neural network,Active safety system,Belief update,Probabilistic classification

论文评审过程:Available online 12 August 2009.

论文官网地址:https://doi.org/10.1016/j.eswa.2009.07.070