采用柯西分解降噪的目标跟踪方法

发布时间：2018-05-22 07:16

本文选题：目标跟踪 + 噪声统计特性　；参考：《计算机工程与应用》2017年17期

【摘要】：提升噪声干扰情况下的目标跟踪精度,提出了一种柯西分解改进的无迹H∞滤波方法。采用UT变换代替传统的泰勒级数线性近似截断处理,降低近似截断误差,提升处理非线性系统的能力;对目标状态的协方差矩阵均方根进行柯西分解,采用对角元素求解,降低了观测噪声的扰动误差对滤波估计精度的影响。仿真结果表明,所提方法明显提升了不同噪声统计特性情况下的跟踪精度和稳定性。
[Abstract]:In order to improve the precision of target tracking under noise interference, a new method of non trace H filtering improved by Cauchy decomposition is proposed. Using UT transform instead of the traditional Taylor series linear approximation truncation, the approximate truncation error is reduced and the ability to improve the processing of nonlinear systems is improved; and the mean square root of the covariance matrix of the target state is decomposed by Cauchy. With the solution of diagonal elements, the influence of the disturbance error of the observed noise on the filtering estimation accuracy is reduced. The simulation results show that the proposed method obviously improves the tracking accuracy and stability of the statistical characteristics of different noise.
【作者单位】：湖北工业大学机械工程学院;湖北工业大学图书管理中心;
【基金】：国家自然科学基金(No.51179197)
【分类号】：TN713

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