An Algorithm for Multitarget Tracking in Dense Clutter

Abstract

Due to some adverse factors, tracking multitarget in dense clutter becomes a difficult task. Therefore, a new algorithm is presented in this paper which consists of m-best 2-D assignment algorithm and generalized likelihood ratio test (GLRT). Simulated numerical examples are given, which demonstrate that this algorithm can solve the problem of "measurement-to-track" association efficiently, and discriminate the true or false track in short time which can reduce the need for storage and calculation enormously