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

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2 Author(s)
Pace, M. ; IRIDIA Artificial Intell. Res. Lab., Univ. Libre de Bruxelles, Brussels, Belgium ; Del Moral, P.

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.

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Selected Topics in Signal Processing, IEEE Journal of  (Volume:7 ,  Issue: 3 )