IMM Method Using GA-Based Intelligent Input Estimation for Maneuvering target Tracking

기동표적 추적을 위한 유전 알고리즘 기반 지능형 입력추정을 이용한 상호작용 다중모델 기법

  • 이범직 (연세대학교 전기전자공학과) ;
  • 주영훈 (군산대학교 전자정보공학부) ;
  • 박진배 (연세대학교 전기전자공학과)
  • Published : 2003.09.01

Abstract

A new interacting multiple model (IMM) method using genetic algorithm (GA)-based intelligent input estimation(IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The GA is utilized to optimize a fuzzy system fur a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation(IE) technique and the adaptive interacting multiple model (AIMM) method.

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