改进粒子滤波算法及其在GPS/SINS组合导航中的应用

Improved Particle Filtering Algorithm and Its Application of the GPS/SINS Integrated Navigation

摘要:

针对标准粒子滤波中存在的粒子退化问题,将无味卡尔曼滤波方法、线性规划方法与标准粒子滤波相结合,得到一种改进粒子滤波算法。改进粒子滤波算法中的重要性概率密度通过 UKF算法获得,从而使粒子使用效率得到提升；二次采样过程中加入线性规划方法,保证了粒子的多样性。将改进粒子滤波算法应用于 GPS/SINS组合导航,建立了 GPS/SINS组合导航模型,通过仿真验证了该滤波算法的有效性,使用该算法可使惯性组合导航系统导航精度得到提高。

Abstract:

Due to the degenerac existing in the particle filter, the particle filter algorithm was combined with unscented Kal.man filter (UKF) algorithm and linear optimization method in this paper. Unscented Kalman filter algorithm was used togenerate the importance proposal distribution, and the linear optimization method was used to enhance the diversity of thesamples. A demonstration system for the GPS/SINS integrated navigation was constructed according to the characteristicsof GPS/SINS integrated navigation system. Simulation results verified the effectiveness of the filtering method and the filter.ing method could improve the navigation accuracy.