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Multi-sensor management: Optimal allocation of tracking resources for Pd < 1 based on the interacting multiple model modified kalman filter

机译:多传感器管理:基于交互多模型修正卡尔曼滤波器的P d <1跟踪资源的最佳分配

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This paper presents a novel sensor selection algorithm for optimal allocation of target tracking resources, based on the interacting multiple model modified kalman filter. The algorithm can be easily calculated and it is possible to include sensors with a probability of detection pd <1. The sensor selection measure function is the minimum trace of covariance matrix. The performance of the sensor selection algorithm is studied for single sensor and sensor collocation. And simulation shows the method is effective and feasible.
机译:本文提出了一种基于交互多模型改进卡尔曼滤波器的最优目标跟踪资源分配的传感器选择算法。该算法可以很容易地计算出,并且可能包括具有检测概率p d <1的传感器。传感器选择量度函数是协方差矩阵的最小迹线。针对单个传感器和传感器并置,研究了传感器选择算法的性能。仿真结果表明该方法是有效可行的。

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