CNS/SINS组合导航系统的UKF算法研究

天文/捷联惯性（CNS/SINS）组合导航系统采用姿态组合，可使姿态角处于收敛状态，并有效抑制位置及速度的发散。为提高组合导航系统的精度，本文设计了CNS/SINS组合导航系统的UKF算法，在建立CNS/SINS组合导航系统非线性状态方程及线性量测方程的基础上，首先对UKF的量测更新过程进行简化，降低其计算量；然后，基于平台误差角提出系统状态协方差矩阵中姿态角协方差矩阵的计算方法，并推导了UKF算法中姿态量测值一步预测误差对应的平台角误差向量表达式，进而建立CNS/SINS组合导航系统的UKF算法；最后进行仿真实验。结果表明，相对于线性卡尔曼滤波算法及EKF算法，本文算法可明显提高组合导航系统的各导航参数精度，并且本文算法对滤波器初始姿态角误差变化具有较高的鲁棒性。

Research on UKF Algorithm of CNS/SINS Integrated Navigation System

The attitude combination of celestial navigation/Strapdown inertial(CNS/SINS) integrated navigation system can make the attitude angle converge and restrain the divergence of position and velocity effectively. To improve the accuracy of the integrated system, we design the UKF algorithm of CNS/SINS integrated navigation system. Firstly, this paper simplifies the measurement update process of UKF algorithm and reduces the computation of UKF, based on the establishment of nonlinear state equation and linear measurement equation of CNS/SINS integrated navigation system. Then, we propose one calculation method of attitude covariance matrix in system state covariance matrix based on platform angle error, which derives the expression of platform angle error vector corresponding to prediction error of attitude measurement value in UKF algorithm, and then establishes the UKF algorithm of CNS/SINS integrated navigation system. Finally, the simulation results show that the proposed algorithm can significantly improve the accuracy of navigation parameters of the integrated navigation system as compared with the linear Kalman filter algorithm and EKF algorithm, and that the proposed algorithm has high robustness to the change the initial attitude angle error of the filter.