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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.