Skip to Main Content
This paper presents a 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 mathematically consistent likelihood function derived from random finite set theory. A particle implementation of the proposed filter is given. Under linear Gaussian assumptions, an exact closed form solution to the proposed recursion is derived, and efficient implementations are given.
Date of Conference: 1-3 Oct. 2007