Data association and target identification using range profile

Abstract

We present a new data association algorithm using range-profile, which has maneuver-following capability. In this approach, targets can be identified as a by-product of the data association, not requiring a separate step for target identification. Early data association cannot identify targets and thus requires a large amount of computation not to miss tracks when targets maneuver and cross each other. Our method using range profile mitigates the complexity of data association. And once the classes of tracks are identified, the tracks can be more efficiently tracked and associated even when target maneuvers. Furthermore, our approach can provide the optimum tracking filter gain for tracking maneuvering target and thus will contribute to the improvement of performance for maneuvering target tracking. Extensive computer simulations have demonstrated that the new data association is not only more efficient in terms of the computational complexity without requiring a separate step for target identification, but also can provide the optimum tracking filter gain for tracking maneuvering target. (C) 2003 Elsevier B.V. All rights reserved.