基于BDS/GSM-R组合列车定位方法的研究
Study of train positioning method based on BDS/GSM-R combination

针对卫星定位容易丢失信号的问题,提出北斗卫星导航技术与GSM-R技术相结合的定位方法。根据哈尔滨西至长春铁路线的实测数据,利用BP神经网络构造BDS/GSM-R定位信息的融合模型,采用遗传算法优化BP神经的权值和阈值,对比优化前和优化后的BDS/GSM-R组合定位方法。实验结果表明:优化后的BP神经网络训练结果与列车实际运行轨迹偏差更小,东向、北向、方位角定位误差的波动范围明显减小,可以保持列车定位的连续性和精确性。
Aiming at the problem that satellite positioning signal is easily lost, the positioning method that combine BeiDou satellite navigation technology with GSM-R technology was put forward. According to the measured data from the Harbin West railway station to Changchun,onethe BDS/GSM-R positioning information fusion model was firstly built using BP neural network structure. The BP neural weights and thresholds were optimized using genetic algorithm. Finally, the results before and after optimization of combined BDS/GSM-R positioning method was compared. . The results show that the difference between the training results of BP neural network after optimization and the practical operation tracks of train is reduced. The range of error located in the east and northoriention and azimuth error are obviously decreased.This method can keep the continuity and precision of train positioning