Comparison of PHD based filters for the tracking of 3D aerial and naval scenarios

Michele Pace 1
1 ALEA - Advanced Learning Evolutionary Algorithms
Inria Bordeaux - Sud-Ouest, UB - Université de Bordeaux, CNRS - Centre National de la Recherche Scientifique : UMR5251
Abstract : The Probability Hypothesis Density (PHD) filter is applied to realistic three-dimensional aerial and naval scenarios to illustrate its performance in detecting, initiating and terminating tracks in presence of clutter. Radar measurements are available every two seconds. A comparisons between different approximations of the PHD recursion, namely the sequential Monte Carlo and the Gaussian Mixture approximation, is given on different scenarios using the OSPA metric and different levels of clutter.
Type de document :
Communication dans un congrès
IEEE Radar Conference, May 2010, Washington, United States. 2010, 〈10.1109/RADAR.2010.5494574〉
Liste complète des métadonnées

https://hal.inria.fr/inria-00535931
Contributeur : Francois Caron <>
Soumis le : dimanche 14 novembre 2010 - 10:48:57
Dernière modification le : jeudi 11 janvier 2018 - 06:22:36

Identifiants

Collections

Citation

Michele Pace. Comparison of PHD based filters for the tracking of 3D aerial and naval scenarios. IEEE Radar Conference, May 2010, Washington, United States. 2010, 〈10.1109/RADAR.2010.5494574〉. 〈inria-00535931〉

Partager

Métriques

Consultations de la notice

231