Random sets in data fusion problems

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Abstract
A general theory of multi-object state-estimation problems, also known as multi-target tracking problems, is presented, using explicit random-set formalism. Probability density functions of random sets, as well as Choquet's capacity functionals, are used to represent random sets, in pursuit of the possibility of such a theory becoming a theoretical foundation of data fusion theory. The theoretical and algorithmic developments over the past three decades in this area are also re-examined in the light of this new formalism, as well as the recent development of correlation-free algorithms that utilize random-set formalism explicitly.

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