基于无迹卡尔曼滤波的BDS/INS组合定位方法

BDS/INS integrated positioning method based on unscented Kalman filter

摘要

针对车辆载体使用惯性导航系统（inertial navigation system，INS）时定位误差随时间而累积以及北斗卫星导航系统（BeiDou navigation satellite system，BDS）信号易受干扰影响定位精度和可靠性的问题，通过分析惯导定位、空间杆臂和时间不同步的误差，建立BDS/INS组合定位状态方程，研究基于无迹卡尔曼滤波（unscented kalman filter，UKF）的BDS/INS组合导航信息融合算法，并对算法进行验证。结果表明，UKF组合导航算法的定位性能优于扩展卡尔曼滤波（extended kalman filter，EKF）算法，其纬度与经度参数的均方根误差比EKF算法减小75.3%与83.8%，提升了BDS/INS组合定位精度。

Abstract

Aiming at the problem that the positioning error accumulates with time when the vehicle carrier uses the inertial navigation system（INS），and the BeiDou satellite navigation system （ BDS ） signal is susceptible to interference， the positioning accuracy and reliability are affected.By analyzing the errors of inertial navigation positioning，space arm and time asynchronous， BDS/INS integrated navigation state equation was established by analyzing the inertial positioning error，space arm error and time asynchronous error，and a BDS/INS integrated navigation information fusion algorithm based on unscented kalman filter（UKF） was obtained.The simulation results show that this integrated navigation method is superior to extended kalman filter （EKF） integrated navigation algorithm，and the root mean square error of latitude and longitude decrease by 75.3% and 83.8% compared with EKF algorithm.The accuracy and reliability of navigation and positioning are improved and the cumulative error of inertial navigation is reduced.

关键词

北斗卫星导航系统 / 惯性导航系统 / 组合定位 / 无迹卡尔曼滤波 / 定位误差

Key words

BeiDou navigation satellite system / inertial navigation system / integrated positioning / unscented Kalman filter / positioning error

基金资助

国家自然科学基金(62173237)

工信部民机专项(01020220627066-3)

辽宁省重点研发计划项目(2020JH2/10100045)

辽宁省应用基础研究计划项目(2022063)