PROJECT TITLE :
High manoeuvre target tracking in coordinated turns
In target tracking, most tracking algorithms are model based mostly, and heavy errors can arise when the models fail to fit the physical target motions, especially throughout coordinated turns. To deal with this problem, a two-step tracking algorithm is proposed. Initial, considering the variety of the target manoeuvres, 5 elemental Singer models with fastidiously designed parameter α interact with every different in an interacting multiple model (IMM) algorithm to accomplish the tracking and estimate the target's kinematic parameters. Second, if a turn motion happens, then it discriminates the flip motion into a horizontal flip or a three-dimensional (3D) flip; and the real-time flip rate is calculated to refine the corresponding model for tracking. Since the filtering stage is vital in estimating the kinematic parameters, sparse-grid quadrature Kalman filter is used to enhance 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.
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