卡尔曼/粒子组合滤波在GPS/INS组合导航中的应用研究

在非线性模型和非高斯噪声条件下，粒子滤波在GPS/INS组合导航系统的观测精度较低时能取得较好的滤波结果，但在高观测精度情况下会导致滤波发散。针对这一问题，在分析了基本粒子滤波器算法原理的基础上提出一种卡尔曼/粒子组合滤波方法，将状态向量分为线性部分和非线性部分，分别用卡尔曼滤波和粒子滤波估计，既保证了简化后滤波算法的结果不会变差，又将运算量大大降低，仿真试验表明，组合滤波器能够获得较高的滤波精度，满足实际的导航要求。

Research on Kalman/particle Filter Applied in Integrated Navigation System

In nonlinear and non-Gaussian integrated navigation system,the standard particle filter is effective when the observations are not accurate,but it is ineffective and diverges more greatly when the measurements are accurate.In this paper,a Kalman/particle filter is proposed to improve the stability of the filter.The new method divides the system into two sub-models:One is linear,and the other one is nonlinear.Then Kalman filter and particle filter are implemented separately.The results of simplified algorithm was not bad but also greatly reduced the computation.Simulation results show the integrated filter is steady and accurate which satisfies the demand for practical navigation.