On the concept of possibility-probability consistency
Fuzzy Sets and Systems
On probability-possibility transformations
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy logic approach to multisensor data association
Mathematics and Computers in Simulation
Maximum entropy fuzzy clustering with application to real-time target tracking
Signal Processing - Special section: Distributed source coding
Application of the EM algorithm for the multitarget/multisensortracking problem
IEEE Transactions on Signal Processing
On the representation, measurement, and discovery of fuzzy associations
IEEE Transactions on Fuzzy Systems
Information Sciences: an International Journal
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This paper proposes a novel all-neighbor fuzzy association approach for multitarget tracking in a cluttered environment. It performs data association with a little prior knowledge and updates the predicted target state estimate using a fuzzy weighted sum of innovations. Unlike the joint probabilistic data association filter, in which the similarity measures are determined in terms of the conditional probability for all feasible data association hypothesis, the proposed fuzzy association approach determines the similarity measures between measurements and tracks in terms of possibility weights based on a partition matrix. The possibility weights are determined according to the fuzzy clustering algorithm. The proposed approach is able to perform all-neighbor association with a lower computational complexity in the expense of a little lower performance compared to the standard joint probabilistic data association filter. Computer simulation shows the feasibility and the efficiency of the proposed all-neighbor fuzzy association approach.