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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Noh, S.Y., Park, J.B., Joo, Y.H. (2006). IMM Method Using Tracking Filter with Fuzzy Gain. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_72
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DOI: https://doi.org/10.1007/11925231_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49026-5
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