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This study is concerned with risk-sensitive filtering and smoothing for a class of discrete-time jump Markov non-linear systems. Using the so-called reference probability method, the authors present a general theoretical framework to yield recursions for deriving filtered and smoothed estimates through identifying the approximations made by the interacting multiple model (IMM) estimation approach. A suboptimal risk-sensitive filtering algorithm is developed by applying the unscented transform (UT) technique and the one-step fixed-lag smoothing result is also presented for such systems. The effectiveness of the proposed algorithms is demonstrated via a manoeuvering target tracking simulation study.
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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2009.0399
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