OPTICS-Based Passive Tracking Algorithm for High Maneuvering Targets

For the high maneuvering target, its motion mode is unknown in advance, so the passive target tracking algorithm using fixed motion model or interactive multi-model cannot match the actual motion mode of the maneuvering target. In order to solve the problem of low tracking accuracy caused by unknown motion model of high maneuvering targets, an OPTICS-based passive tracking algorithm for high maneuvering targets was proposed. The algorithm estimates the target state by using the OPTICS trajectory clustering algorithm when the tracking error is large, and updates the state transition matrix based on the motion model estimates and multi-station passive sensor observations. The simulation results verify that the OPTICS-based passive tracking algorithm for high maneuvering targets proposed in this paper can effectively improve the tracking accuracy of high maneuvering targets, which is beneficial to the realization of low probability of interception tracking.