改进的强跟踪卡尔曼滤波器在MSINS/GPS组合导航中的应用研究  

Research on Improved Strong Tracking Kalman Filter in MSINS/GPS Integrated Navigation System

作　　者：马云峰[1] 

机构地区：[1]潍坊学院,山东潍坊261061

出　　处：《潍坊学院学报》2014年第2期1-5,共5页Journal of Weifang University

基　　金：山东省科学技术发展计划(2011YD01052)

摘　　要：通过深入分析次优渐消因子的解算原理,提出了一种无须先验知识的多时变渐消因子估计方法,用于改进强跟踪卡尔曼滤波算法,并将其应用于MSINS/GPS浅组合中。采用多个次优渐消因子,分别对不同的数据通道进行渐消,可以有效提高滤波算法的跟踪能力。仿真结果表明,改进的强跟踪卡尔曼滤波算法解决了量测相关、初值选取敏感性等问题,可以提高系统的实时性、鲁棒性。Through embedded analysis of the calculating principles of suboptimal fading factors,this dissertation puts forward a method of time varying fading factors estimation without a prior knowledge.This method has been used to improve the strong tracking Kalman filter algorithm and applied to loose coupling system of MSINS/GPS integrated navigation.Respectively to fade different data channel with several suboptimal fading factors,it can effectively improve the tracking ability of the filtering algorithm.The simulation results show that this approach can resolve the problem of the measurement correlation and the sensitivity of initial values selecting.The real time character and robust of the system has been improved.

关 键 词：捷联惯导系统 全球定位系统 组合导航 卡尔曼滤波 强跟踪 渐消因子 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计]