High manoeuvre target tracking in coordinated turns

Abstract

In target tracking, most tracking algorithms are model based, and serious errors can arise when the models fail to fit the physical target motions, especially during coordinated turns. To address this problem, a two-step tracking algorithm is proposed. First, considering the diversity of the target manoeuvres, five elemental Singer models with carefully designed parameter α interact with each other in an interacting multiple model (IMM) algorithm to accomplish the tracking and estimate the target's kinematic parameters. Second, if a turn motion occurs, then it discriminates the turn motion into a horizontal turn or a three-dimensional (3D) turn; and the real-time turn rate is calculated to refine the corresponding model for tracking. Since the filtering stage is important in estimating the kinematic parameters, sparse-grid quadrature Kalman filter is employed to improve the filtering capability. The proposed algorithm is exemplified by simulation tests and data tests in 3D, and is compared with that of an IMM algorithm utilising constant velocity, constant acceleration and 3D coordinated turn models. All of the test results demonstrate that the proposed algorithm is effective and has higher accuracy.