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Mean-Field PHD Filters Based on Generalized Feynman-Kac Flow | IEEE Journals & Magazine | IEEE Xplore

Mean-Field PHD Filters Based on Generalized Feynman-Kac Flow


Abstract:

We discuss a connection between spatial branching processes and the PHD recursion based on conditioning principles for Poisson Point Processes. The branching process form...Show More

Abstract:

We discuss a connection between spatial branching processes and the PHD recursion based on conditioning principles for Poisson Point Processes. The branching process formulation gives a generalized Feynman-Kac systems interpretation of the PHD filtering equations, which enables the derivation of mean-field implementations of the PHD filter. This approach provides a principled means for obtaining target tracks and alleviates the need for pruning, merging and clustering for the estimation of multi-target states.
Published in: IEEE Journal of Selected Topics in Signal Processing ( Volume: 7, Issue: 3, June 2013)
Page(s): 484 - 495
Date of Publication: 07 March 2013

ISSN Information:


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