• 제목/요약/키워드: time-varying mode transition probabilities

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Design of Fuzzy IMM Algorithm based on Basis Sub-models and Time-varying Mode Transition Probabilities

  • Kim Hyun-Sik;Chun Seung-Yong
    • International Journal of Control, Automation, and Systems
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    • 제4권5호
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    • pp.559-566
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    • 2006
  • In the real system application, the interacting multiple model (IMM) based algorithm requires less computing resources as well as a good performance with respect to the various target maneuverings. And it further requires an easy design procedure in terms of its structures and parameters. To solve these problems, a fuzzy interacting multiple model (FIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as inputs of a fuzzy decision maker, is proposed. To verify the performance of the proposed algorithm, airborne target tracking is performed. Simulation results show that the FIMM algorithm solves all problems in the real system application of the IMM based algorithm.

Design of Adaptive Fuzzy IMM Algorithm for Tracking the Maneuvering Target with Time-varying Measurement Noise

  • Kim, Hyun-Sik;Kim, In-Ho
    • International Journal of Control, Automation, and Systems
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    • 제5권3호
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    • pp.307-316
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    • 2007
  • In real system application, the interacting multiple model (IMM) based algorithm operates with the following problems: it requires less computing resources as well as a good performance with respect to the various target maneuvering, it requires a robust performance with respect to the time-varying measurement noise, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as the inputs of the fuzzy decision maker whose widths are adjusted, is proposed. To verify the performance of the proposed algorithm, a radar target tracking is performed. Simulation results show that the proposed AFIMM algorithm solves all problems in the real system application of the IMM based algorithm.