基于平方根UKF的伪卫星 动态跟踪定位算法
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中国电子科技集团公司第五十四研究所

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高可用安全导航标准模块研


Pseudolite dynamic tracking and positioning algorithm based on square root UKF
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Research on high availability safety navigation standard module

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    摘要:

    结合动态导航系统中的目标跟踪定位问题,针对传统Kalman滤波在处理非线性系统时的局限性以及扩展卡尔曼滤波(Extended Kalman Filter,EKF)在处理强非线性系统时的发散性以及精度较差的问题,在不敏卡尔曼滤波(Unscented Kalman Filter,UKF)算法的基础上提出了一种基于平方根UKF的动态跟踪定位算法。为了提高滤波算法的滤波效率以及滤波精度,在递推运算的过程中用协方差矩阵的平方根来替代传统算法计算过程中的协方差矩阵,由MATLAB仿真结果可以看出平方根UKF算法相比于EKF算法精度提升了54.7%,相比于UKF算法精度提升了14.8%。

    Abstract:

    Considering the problem of target tracking and positioning in dynamic navigation system, aiming at the limitation of traditional Kalman filter in dealing with nonlinear system and the problem of divergence and poor accuracy of extended Kalman filter (EKF) in dealing with strong nonlinear system, the unscented Kalman filter (unscented Kalman filter) is proposed Based on the filter (UKF) algorithm, a dynamic tracking and positioning algorithm based on square root UKF is proposed. In order to improve the filtering efficiency and accuracy of the filtering algorithm, the square root of the covariance matrix is used to replace the covariance matrix in the calculation process of the traditional algorithm in the recursive operation process. The MATLAB simulation results show that the accuracy of the square root UKF algorithm is 54.7% higher than that of the EKF algorithm, and 14.8% higher than that of the UKF algorithm.

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  • 收稿日期:2020-08-09
  • 最后修改日期:2020-08-09
  • 录用日期:2023-09-20
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