利用RTS平滑算法分析BDS/GNSS定位精度

An assessment of BDS/GNSS positioning accuracy based on RTS backward smoothing methods

为解决精密单点定位技术(PPP)收敛阶段精度差的问题,本文研究了利用RTS反向平滑算法提高定位精度。首先,基于前向Kalman滤波算法进行前向PPP解算,精度统计表明BDS在N、E、U分量定位精度分别为2.6、2.0、7.8 mm,采用GPS+Galileo系统组合解算的精度最优,其在N、E、U方向的定位精度可达到1.7、2.1、3.4 mm。基于RTS反向平滑算法的动态PPP分析表明,单BDS系统在N、E、U方向的定位精度可达到3.3、3.4、9.0 mm。加入GPS、GLONASS或Galileo观测值后BDS定位精度提升达50%以上。车载动态试验分析进一步表明,采用反向RTS平滑算法进行PPP解算在N、E、U 3个方向的定位精度分别可达0.028、0.015和0.033 m。

To mitigate the issue of poor accuracy during the convergence phase of precise point positioning(PPP),we investigates the improvement of positioning accuracy using the RTS(Rauch-Tung-Striebel)backward smoothing algorithm.The evaluation of static PPP using the forward Kalman filter indicates that BDS can achieve an accuracy of 2.6 mm,2.0 mm,7.8 mm in N、E、U direction.The GPS+Galileo combined PPP can achieve the best accuracy,which is 1.7 mm,2.1 mm,3.4 mm in the N、E、U direction.The kinematic PPP using the RTS smoothing method indicate that an accuracy of 3.3 mm,3.4 mm,9.0 mm can be achieved for the BDS PPP in the N、E、U direction.Introducing the GPS,GLONASS,or Galileo observations can improve the accuracy of BDS PPP by more than 50%.The analysis of on-vehicle dynamic testing further indicates that utilizing the reverse RTS smoothing algorithm for PPP calculations can achieve positioning accuracies of 0.028 meters in the north direction(N),0.015 meters in the east direction(E),and 0.033 meters in the up direction(U).