Embedded track validation for tree search-based tracking of maneuvering targets

We propose an integrated track validation scheme for tree search-based target tracking. Embedded within the search algorithm, the proposed approach improves the robustness of tree search-based tracking in the presence of uncertain target motion models and heavy clutter. A likelihood ratio test is employed for each track estimate considered (e.g. each path in the search tree), and those falling below a threshold are eliminated. By pruning unlikely target paths from the search tree, the embedded track validation algorithm decreases the memory requirement of the tracker while concurrently improving tracking precision. Simulation results reveal improved tracker performance and demonstrate the effect of clutter and target maneuvers on the likelihood ratio.