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

作者：Park Seongkeun; Hwang Jae Pil; Kim Euntai^*; Lee Heejin; Jung Ho Gi

来源：Expert Systems with Applications, 2010, 37(3): 2340-2346.

DOI：10.1016/j.eswa.2009.07.070

• Target classification
• Multilayer perceptron neural network
• Active safety system
• Belief update
• Probabilistic classification

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.

• 出版日期2010-3-15