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

作　　者：王林[1,2] 林雪原[1] 孙炜玮[1] 王萌[1] 

机构地区：[1]海军航空工程学院信息融合研究所 [2]92154部队

出　　处：《海军航空工程学院学报》2016年第1期51-57,共7页Journal of Naval Aeronautical and Astronautical University

基　　金：国家自然科学基金资助项目(60874112)

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

关 键 词：惯性组合导航 无迹卡尔曼滤波 线性规划 粒子滤波 

分 类 号：V249.328[航空宇航科学与技术—飞行器设计]