基于平方根UKF的伪卫星动态跟踪定位算法

为了解决传统Kalman滤波在处理非线性系统时的局限性，以及扩展Kalman滤波（EKF）在处理强非线性系统时发散性和精度较差的问题，结合动态导航系统中的目标跟踪定位问题，在不敏Kalman滤波（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，在递推运算过程中采用协方差矩阵的平方根代替传统算法计算过程中的协方差矩阵。MATLAB仿真结果表明，平方根UKF算法的精度比EKF提升了54.7%，比UKF提升了14.8%。所提出的算法解决了Kalman处理非线性系统的局限性以及传统EKF和UKF算法精度不高的问题，为伪卫星系统的高精度定位研究提供了有力支撑。

Pseudolite dynamic tracking and positioning algorithm based on square root UKF

In order to solve 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, a dynamic tracking and positioning algorithm based on square root UKF was proposed based on the unscented Kalman filter (UKF) algorithm in combination with the problem of target tracking and positioning in dynamic navigation system. In the process of recursive operation, the square root of covariance matrix was used to replace the covariance matrix in the calculation process of covariance algorithm. 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. The proposed algorithm solves the limitation of Kalman processing nonlinear system and the problem of the low accuracy of traditional EKF and UKF algorithms, and provides a strong support for the high-precision positioning of pseudolite system.