Abstract
A multiple model algorithm based on fuzzy sets is introduced as an alternative to the Interacting Multiple Model Algorithm(IMMA) and the Adaptive Interacting Multiple Model Algorithm(AIMMA) for tracking manoeuvring targets. An augmented state filter provides estimates of the target acceleration, and using these estimates model weightings are obtained from membership values of fuzzy sets. By arranging the overlap of these fuzzy sets, the number of filters operating, and hence the computational load, can be significantly reduced. Simulation results presented suggest comparable performance to IMMA and AIMMA during manoeuvres, with improved performance during nonmanoeuvre, constant velocity periods.
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