Kalman滤波在GPS/BDS组合伪距差分定位中的应用

Application of Kalman Filtering in Pseudo Range Differential Positioning in GPS/BDS Combination

摘要:

随着各国卫星导航系统的蓬勃发展，单一的GPS系统时代正逐步转变为多系统并存且兼容的全球性卫星导航系统（GNSS）时代。相比于单一卫星导航系统，多系统组合将显著增加可视卫星数目、改善卫星空间几何结构，多系统组合导航定位将是必然的发展趋势。滤波算法是减小GNSS定位随机误差的重要方法，利用非线性滤波方法可消除多种随机误差，从而提高导航定位精度。该文实现了基于Kalman滤波的GPS/BDS组合的伪距差分定位，并将其与最小二乘方法进行比较。实验结果表明：基于Kalman滤波的GPS/BDS伪距差分的定位精度能达到分米级，在差分定位解算过程中，多卫星系统伪距差分精度明显优于单卫星系统伪距差分精度，Kalman滤波解算的精度明显优于最小二乘解算的精度。

Abstract:

Accompanying with rapid development of the satellite navigation system, the single GPS system era is gradually transformed into a compatible multi global satellite navigation system (GNSS) era. Comparing with the single satellite navigation system, the combination of multiple systems will significantly increase the number of visible satellites and improve the geometric structure of satellite space. Multi system integrated navigation and positioning will be an inevitable trend. The filtering algorithm is an important method to reduce the random error of GNSS positioning. By using nonlinear filtering method, great majority of random errors can be eliminated, the precision of navigation can be improved. In this paper, the pseudo range differential positioning of GPS/BDS combination based on Kalman filtering is implemented and compared with the least square method. The experimental results show that the accuracy of the GPS/BDS pseudo range differential positioning based on Kalman filtering can reach the decimeter level. In the process of differential positioning, the pseudo range precision of the multi satellite system is obviously better than that of the single satellite system. The accuracy of the Kalman filtering solution is obviously superior to that of the least squares solution.