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• W2147577240 abstract "Traditional multihypothesis tracking methods rely upon an enumeration of all the assignments of measurements to tracks. Pruning and gating are used to retain only the most likely hypotheses in order to drastically limit the set of feasible associations. The main risk is to eliminate correct measurement sequences. The probabilistic multiple hypothesis tracking (PMHT) method has been developed by Streit and Luginbuhl in order to reduce the drawbacks of strong assignments. The PMHT method is presented in a general mixture densities perspective. The Expectation-Maximization (EM) algorithm is the basic ingredient for estimating mixture parameters. This approach is then extended and applied to multitarget tracking for nonlinear measurement models in the passive sonar perspective." @default.
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• W2147577240 date "1997-10-01" @default.
• W2147577240 modified "2023-09-27" @default.
• W2147577240 title "A formulation of multitarget tracking as an incomplete data problem" @default.
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• W2147577240 doi "https://doi.org/10.1109/7.625121" @default.
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