发射系下的SINS/CNS/GNSS组合导航UKF滤波算法

弹载系统的组合导航系统模型常建立在发射惯性坐标系下，且捷联惯性/天文导航/卫星导航（SINS/CNS/GNSS）是一种目前研究较多的组合模式。该组合导航系统的状态方程具有强非线性的特点，常用的滤波方法为扩展卡尔曼滤波（EKF）。为了提高组合导航系统的精度及可靠性，对该组合导航系统的无迹卡尔曼滤波（UKF）模型进行了设计，直接将姿态、位置与速度参数作为状态的一部分，利用CNS及GNSS提供的姿态与位置构成量测方程，并详细给出了姿态样本点的生成、均值及方差的生成过程。仿真结果表明，相对于EKF算法，采用UKF算法后各导航参数的精度可提高约20%~30%，并且系统的实时性也可以得到保证。

UKF filtering algorithm for SINS/CNS/GNSS integrated navigation in launch inertial coordinate system

The integrated navigation system model of missile system is often established under the launch inertial coordinate system, and the strapdown inertia/celestial navigation/satellite navigation (SINS/CNS/GNSS) is one of the most studied integrated modes. The state equation of the integrated navigation system is strongly nonlinear, and the common filtering method is extended Kalman filtering (EKF). In order to improve the precision and reliability of integrated navigation system, the UKF filter model of the integrated navigation system was designed, directly using the attitude, position and velocity parameters as part of the state, and the attitude and position provided by CNS and GNSS to form the measurement equation.The generation process of attitude sample points, mean value and variance was given. Simulation results show that, compared with EKF algorithm, UKF algorithm can improve the accuracy of navigation parameters by about 20%~30%, and that the real time performance of the system can be guaranteed.