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

Authors:
Seongkeun Park;Jae Pil Hwang;Euntai Kim;Heejin Lee;Ho Gi Jung
Affiliations:
School of Electrical and Electronic Engineering, Yonsei University, C613, Sinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea;School of Electrical and Electronic Engineering, Yonsei University, C613, Sinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea;School of Electrical and Electronic Engineering, Yonsei University, C613, Sinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea;Department of Information and Control Engineering, Hankyong National University, Republic of Korea;Mando Central Research Center, Gyeonggi-do 449-901, Republic of Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

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 24GHz 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.