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Maneuvering Target Tracking Algorithm based on Current Statistical Model in Three Dimensional Space

机译:基于当前统计模型的三维空间机动目标跟踪算法

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摘要

This paper is mainly to solve the problems associated with maneuvering target tracking based current statistical model in three dimensional space. Firstly, a three-dimensional model of the nine state variables is presented. Then adaptive Kalman filtering algorithm is designed with the motor acceleration data mean and variance. Finally, A simulation about the adaptive Kalman filtering put forward by this thesis and the direct calculation method is given,which aim at the maneuvering target in three-dimension. The results show the good performances such as better target position, velocity and acceleration estimates brought by the proposed approach by presenting and discussing the simulation results.
机译:本文的主要目的是解决在三维空间中与基于机动目标跟踪的当前统计模型有关的问题。首先,提出了九个状态变量的三维模型。然后利用电机加速度数据的均值和方差设计自适应卡尔曼滤波算法。最后,针对三维机动目标,给出了本文提出的自适应卡尔曼滤波仿真和直接计算方法。结果通过展示和讨论仿真结果,表明了该方法带来的良好性能,例如更好的目标位置,速度和加速度估计。

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