IMM Method Using Tracking Filter with Fuzzy Gain

  • Sun Young Noh
  • Jin Bae Park
  • Young Hoon Joo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)


In this paper, we propose an interacting multiple model (IMM) method using intelligent tracking filter with fuzzy gain to reduce tracking error for maneuvering target. 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 an acceleration input is detected, the state estimate for each sub-model is 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). Finally, the tracking performance of the proposed method is compared with those of the input estimation(IE) method and AIMM method through computer simulations.


Fuzzy System Fuzzy Rule Kalman Gain Acceleration Level Acceleration Input 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sun Young Noh
    • 1
  • Jin Bae Park
    • 1
  • Young Hoon Joo
    • 2
  1. 1.Yonsei UniversitySeoulKorea
  2. 2.Kunsan National University, KunsanChunbukKorea

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