한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)

한국지능시스템학회 (Korean Institute of Intelligent Systems)
권호 표지

퍼지 게인을 갖는 칼만필터를 이용한 IMM 기법

IMM Method Using Kalman Filter with Fuzzy Gain

  • 노선영 (연세대학교 전기전자공학과) ;
  • 주영훈 (군산대학교 전자정보공학부) ;
  • 박진배 (연세대학교 전기전자공학과)
  • Hoh Sun-Young (Dept. of Electrical & Electronic Eng., Yonsei University) ;
  • Joo Young-Hoon (School of Electronic & Information Eng., Kunsan University) ;
  • Park Jin-Bae (Dept. of Electrical & Electronic Eng., Yonsei University)
  • 발행 : 2006.05.01
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초록

In this paper, we propose an interacting multiple model (IMM) method using intelligent tracking filter with fuzzy gain to reduce tracking errors for maneuvering targets. In the proposed filter, to exactly estimate for each sub-model, we propose the fuzzy gain based on the relation between the filter residual and its variation. To optimize each fuzzy system, we utilize the genetic algorithm (GA). Finally, the tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and input estimation (IE) method through computer simulations.

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