Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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IMM Method Using Kalman Filter with Fuzzy Gain

  • Noh, Sun-Young (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Joo, Young-Hoon (School of Electronic and Information Engineering, Kunsan National University) ;
  • Park, Jin-Bae (Department of Electrical and Electronic Engineering, Yonsei University)
  • Published : 2006.04.01
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Abstract

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, the unknown acceleration input for each sub-model is determined by mismatches between the modelled target dynamics and the actual target dynamics. After a acceleration input is detected, the state estimates for each sub-filter are modified. To modify the accurate estimation, 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). 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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References

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