激光捷联惯导系统/地形辅助导航系统中卡尔曼/粒子组合滤波算法设计及仿真

粒子滤波技术是近几年出现的一种非线性滤波技术，它适用于非线性系统以及非高斯噪声模型。结合粒子滤波和卡尔曼滤波各自的优点，给出了一种卡尔曼／粒子组合滤波器，并将这种滤波器应用到激光捷联惯导（LSINS）／地形辅助导航（TAN）数据融合过程中，避免了地形复杂的线性化问题。仿真结果表明，系统的定位精度得到了明显提高。应用粒子滤波器及其改进算法解决了导航系统中存在的强非线性问题。

Kalman/particle filter''''s design and simulation in LSINS/TAN

The particle filtering is a nonlinear filtering technology, which is suitable for the nonlinear system and non-Gaussian noise model. In this paper, a Kalman/particle filter combining the advantages of both filters is presented and applied to the data fusion of LSINS/TAN integrated system, so the complicated iinearization Of terrain is avoided. Simulation results show that the precision of the integrated system has been improved remarkably. The strong nonlinearity of navigation system is solved using the particle filtering and its improved algorithm.