Bayesian Filtering With Random Finite Set Observations

Bayesian Filtering With Random Finite Set Observations

This paper presents a novel and mathematically rigorous Bayes’ recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clutter. Our Bayesian formulation is mathematically well-founded due to our use of a consistent likelihood function derive...

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Bibliographic Details
Main Authors: Vo, Ba Tuong, Vo, Ba-Ngu, Cantoni, Antonio
Format: Journal Article
Published: IEEE 2008
Subjects:
PHD filter
Kalman filter
target tracking
point processes
Gaussian sum filter
CPHD filter
particle filter
Bayesian filtering
random finite sets
Online Access:http://hdl.handle.net/20.500.11937/14299

Internet

http://hdl.handle.net/20.500.11937/14299

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