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

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 tired lag) times beyond that of filtering for the original system. In addition, an algorith m that approximates the "fixed-lag" mode probabilities given measurements u p to current time is proposed. The algorithm is illustrated via a target tr acking simulation example where a significant improvement over the filterin g 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 f ixed lag d > 0). The IMM fixed-lag smoothing performance for the given exam ple is comparable to that of an existing IMM fixed-interval smoother. Compa red with fixed-interval smoothers, the tired-lag smoothers can be implement ed in real-time with a small delay.