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Maneuvering Target Tracking Approaches Based on Turning Rate Estimation

机译:基于转弯速率估计的机动目标跟踪方法

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A new class of interacting multiple-model algorithms based on turning rate estimation for maneuvering target tracking is presented. To track turning maneuver, the key is how to estimate the parameter of motion, i.e., target's turning rate. It can be obtained in real time while the target's heading is filtered using multiple motion models, which include current statistical model and constant angular velocity model. Then the result estimated could be integrated with the variation of circular-turn model (VCTM) and the curvilinear model (CM), referred to as modified VCTM (MVCTM) and modified CM (MCM) respectively. The performances of the algorithms presented here are evaluated and compared via simulation of a generic maneuvering target tracking problem. Simulation results show that the MVCTM-based significantly outperform the MCM-based tracker.
机译:提出了一种基于转向速率估计的机动目标跟踪的新型交互多模型算法。为了跟踪转弯动作,关键是如何估计运动参数,即目标的转弯速率。当使用多个运动模型(包括当前统计模型和恒定角速度模型)对目标航向进行过滤时,可以实时获取它。然后将估计的结果与圆转弯模型(VCTM)和曲线模型(CM)的变化集成在一起,分别称为修改后的VCTM(MVCTM)和修改后的CM(MCM)。通过模拟一般机动目标跟踪问题,可以评估和比较此处介绍的算法的性能。仿真结果表明,基于MVCTM的跟踪器明显优于基于MCM的跟踪器。

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