IMM method using tracking filter with fuzzy gain

Authors:
Sun Young Noh;Jin Bae Park;Young Hoon Joo
Affiliations:
Yonsei University, Seoul, Korea;Yonsei University, Seoul, Korea;Kunsan National University, Kunsan, Chunbuk, Korea
Venue:
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Year:
2006

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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 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.