DocumentCode :
1252725
Title :
A formulation of multitarget tracking as an incomplete data problem
Author :
Gauvrit, H. ; Le Cadre, J.-P. ; Jauffret, C.
Author_Institution :
IRISA/CNRS, Rennes, France
Volume :
33
Issue :
4
fYear :
1997
Firstpage :
1242
Lastpage :
1257
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.
Keywords :
numerical analysis; optimisation; parameter estimation; probability; sensor fusion; sonar tracking; target tracking; correct measurement sequences; feasible associations; gating; hypotheses; multihypothesis tracking; multitarget tracking; nonlinear measurement models; passive sonar; probabilistic multiple hypothesis tracking; risk; strong assignments; Array signal processing; Clutter; Filtering algorithms; Iris; Maximum likelihood estimation; Parameter estimation; Radar tracking; Reactive power; Signal processing algorithms; Sonar applications; Sonar measurements; State estimation; Surveillance; Target tracking;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.625121
Filename :
625121
Link To Document :
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