基于抗差估计的BDS/ODO组合列车定位方法
BDS/ODO integrated train positioning method based on robust estimation

根据列车定位的实际需求，采用北斗卫星导航系统和里程计构建列车组合定位系统，利用二者的优势进行互补。针对传统的Kalman滤波算法用于列车组合定位融合估计存在的问题，提出一种基于抗差估计理论的列车组合定位方法。对各传感器观测信息应用抗差估计进行融合解算，利用等价权函数自适应地调节各传感器观测值的比重，有效降低粗差观测值对融合结果的影响。研究结果表明：在传感器观测值含有粗差的情况下，基于抗差估计的组合定位解明显优于常规Kalman滤波解和扩展Kalman滤波解。抗差估计法能增强系统的鲁棒性，提高滤波实时性，保证列车定位的精确性和可靠性。
According to the actual needs of the train positioning, beidou navigation satellite system together with the odometer are used to build the train combination positioning system, which takes the advantages of the two to be complementary. Aiming at the problem of using conventional Kalman filter for the train combination positioning fusion estimation, a train combination positioning method based on robust estimation is proposed. On one hand, the fusion calculation is carried out by applying the robust estimation to the sensor observation information. On the other hand, the equivalent weight function is used to adaptively adjust the proportion of each sensor’s observed value. Therefore, the effects of gross observations on fusion results will be effectively reduced. The simulation results show that, in the case where the sensor observations contain gross errors，the combination positioning solution based on the robust estimation is superior to both the conventional Kalman filter solution and the extended Kalman filter solution. The robust estimation method can enhance the robustness of the system, improve the filter real-time and ensure the accuracy and reliability of the train positioning