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Adaptive tracking of group targets using random matrix

机译:使用随机矩阵对群组目标进行自适应跟踪

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摘要

Adaptive tracking method of group targets using random matrix based on the current statistical model (CS) is presented in order to improve tracking performance of group targets in strong manoeuvring and high measurement error. In the estimation of group centroid, a bell-shape function is utilised as fuzzy membership function to adjust the maximum acceleration which can modify the process noise variance adaptively. The introduction of strong tracking filter with multiple suboptimal fading factors adjusts error covariance of predicted group centroid state adaptively when group targets manoeuvre strongly. In the estimation of group extension, the measurement accuracy is considered in the extended state estimation where the likelihood function is formatted with extended state and measurement error covariance which is calculated by the innovation and adaptive fading memory updated in iterative process. The simulation results show that the method presented in the paper achieves better tracking performance of group targets in strong manoeuvring and high measurement error compared with the existing methods.
机译:为了提高机动性强,测量误差大的群体目标的跟踪性能,提出了基于当前统计模型(CS)的基于随机矩阵的群体目标自适应跟踪方法。在估计组质心时,钟形函数用作模糊隶属函数来调整最大加速度,从而可以自适应地修改过程噪声方差。当组目标强烈机动时,引入具有多个次优衰落因子的强跟踪滤波器可自适应地调整预测组质心状态的误差协方差。在组扩展的估计中,在扩展状态估计中考虑了测量精度,其中,似然函数采用扩展状态和测量误差协方差进行格式化,该误差和协方差由在迭代过程中更新的创新和自适应衰落存储器计算得出。仿真结果表明,与现有方法相比,本文方法在机动性强,测量误差大的情况下,具有较好的群体目标跟踪性能。

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