一种基于改进卡尔曼滤波的GPS/BDS/SINS深组合定位算法  

A GPS/BDS/SINS Deep Positioning Algorithm Based on Improved Kalman Filter

作　　者：陈柯勋 邱伟[2] CHEN Kexun;QIU Wei(College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China;Beijing Institute of Strength & Environment Engineering, Beijing 100076, China)

机构地区：[1]太原理工大学信息与计算机学院,太原030600 [2]北京强度环境研究所,北京100076

出　　处：《太原理工大学学报》2020年第3期446-450,共5页Journal of Taiyuan University of Technology

基　　金：国家自然科学基金资助项目(518050346)。

摘　　要：针对在卫星信号受干扰严重的复杂地貌环境中,由于可见卫星数目较少、卫星信号质量差,导致卫星定位导航精度低的问题,提出了GPS/BDS/SINS深组合定位算法。该算法在GPS/BDS伪距组合定位的基础上,引入惯性器件测量值进行惯导辅助组合定位,借助渐消卡尔曼滤波,通过在线估计量测噪声和系统噪声,进一步降低定位误差,输出高精度定位结果。实验结果表明,本文所述算法相较于传统组合定位算法,定位精度高且计算效率高,具有一定的理论意义和实用价值。In complex geomorphic environments where satellite signals are severely disturbed,satellite positioning and navigation accuracy is low owing to fewer visible satellites and poor satellite signal quality.To solve this problem,a GPS/BDS/inertial navigation deep positioning algorithm is proposed.Based on GPS/BDS pseudo-range combined positioning,this algorithm introduces inertial device measurement values for inertial navigation assisted combined positioning.With the help of fade-out Kalman filtering,it estimates the measurement noise and system noise online to further reduce positioning errors and output high accuracy positioning results.Experimental results show that the algorithm described in this paper has higher theoretical accuracy and higher computational efficiency than traditional combined localization algorithms,and has certain theoretical significance and practical value.

关 键 词：全球卫星导航系统 惯性导航系统 组合定位 卡尔曼滤波 

分 类 号：K826.16[历史地理—历史学]