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改进粒子滤波算法及其在GPS/SINS组合导航中的应用
引用本文:王林,林雪原,孙炜玮,王萌.改进粒子滤波算法及其在GPS/SINS组合导航中的应用[J].海军航空工程学院学报,2016,31(1):51-57.
作者姓名:王林  林雪原  孙炜玮  王萌
作者单位:海军航空工程学院信息融合研究所,山东烟台 264001;92154部队,山东烟台 264007,海军航空工程学院信息融合研究所,山东烟台 264001,海军航空工程学院信息融合研究所,山东烟台 264001,海军航空工程学院信息融合研究所,山东烟台 264001
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。

关 键 词:惯性组合导航  无迹卡尔曼滤波  线性规划  粒子滤波

Improved Particle Filtering Algorithm and Its Application of the GPS/SINS Integrated Navigation
WANG Lin,LIN Xueyuan,SUN Weiwei and WANG Meng.Improved Particle Filtering Algorithm and Its Application of the GPS/SINS Integrated Navigation[J].Journal of Naval Aeronautical Engineering Institute,2016,31(1):51-57.
Authors:WANG Lin  LIN Xueyuan  SUN Weiwei and WANG Meng
Institution:Research Institute of Information Fusion, NAAU, Yantai Shandong 264001, China ;The 92154th Unit of PLA, Yantai Shandong 264007, China,Research Institute of Information Fusion, NAAU, Yantai Shandong 264001, China,Research Institute of Information Fusion, NAAU, Yantai Shandong 264001, China and Research Institute of Information Fusion, NAAU, Yantai Shandong 264001, China
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.
Keywords:inertial integrated navigation  unscented Kalman filter  linear optimization  particle filter
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