Tracking of multiple targets in clutter using optimal sets based on linear programming

This paper is devoted to the problem of tracking multiple targets in clutter and a new methods is presented. We first formulate the data assignments problem of measurement-to-target as a linear programming problem. Through using the linear programming (LP)-based branch-and-bound method and adjusting the constraint conditions, the optimal sets based on linear programming (LP-OS) method is presented then for tracking of multiple targets in clutter. Extensive Monte Carlo simulations show that the presented method can obtain better estimation than the optimization method of linear programming problem, especially, in the situation of multi-clutter and high measurement noise.