We investigate a suboptimal approach to the fixed-lag smoothing problem for Markovian switching systems. A fixed-lag smoothing algorithm is developed by applying the basic Interacting Multiple Model (IMM) approach to a state-augmented system. The computational load is roughly d (the fixed lag) times beyond that of filtering for the original system. In addition, an algorithm that approximates the "fixed-lag" mode probabilities given measurements up to current time is proposed. The algorithm is illustrated via a target tracking simulation example where a significant improvement over the filtering algorithm is achieved at the cost of a time delay (i.e., data up to time k are used to produce the smoothed state estimate at time k-d where the fixed large d>0). the IMM fixed-lag smoothing performance for the given example is comparable to that of an existing IMM fixed-interval smoother. Compared with fixed-interval smoothers, the fixed-lag smoothers can be implemented in real-time with a small delay.


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    Title :

    Interacting multiple model fixed-lag smoothing algorithm for Markovian switching systems


    Contributors:
    Bing Chen, (author) / Tugnait, J.K. (author)


    Publication date :

    2000-01-01


    Size :

    197992 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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