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

Seongkeun Park, Jae Pil Hwang, Euntai Kim, Heejin Lee, Ho Gi Jung

Research output: Contribution to journalArticle

19 Citations (Scopus)

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 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.

Original languageEnglish
Pages (from-to)2340-2346
Number of pages7
JournalExpert Systems with Applications
Volume37
Issue number3
DOIs
Publication statusPublished - 2010 Mar 15

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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