Data Association And Tracking From Distributed Sensors Using Hidden Markov Models And Evidential Reasoning
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We address the problem of tracking targets from distributed sensors in a cluttered environment (see Fig. 1). In a paper which will be presented at IEEE ICASSP-92 we introduced a new method relying on Bayesian theory and HMMs, which is theoretically dedicated to the single target case. We here present a second approach, which is valid in the multiple target case, thanks to the use of Dempster/Shafer’s theory of evidence. Our applicationis, to ourknowledge, an original one for this theory.
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