摘要
列车定位技术已向组合方向发展,组合定位能提高列车的定位精度及定位系统的稳定性,其中,数据融合算法是最关键的技术之一。将DGPS(差分GPS)、应答器、ODO(里程计)定位系统的定位信息采用联邦卡尔曼滤波进行信息融合,采用信息分配因子,决定不同传感器定位信息在组合定位系统中所占的权值,可有效利用各种定位技术的优势;同时给出了算法的理论分析与仿真结果,证明了融合算法的可行性。
Train positioning technology has evolved into the direction of integrated positioning, which can improve the accuracy and stability of train positioning. Therein, the algorithms of data fusion are the most important technology in the integrated positioning system. The Federated Kalman Filtering to fuse the data from DGPS, balise and ODO positioning systems, data sharing factors are defined to determine the weight of positioning data from the sensors in the system. This data fusion algorithm can take advantages of various positioning technologies. Theoretical a- nalysis and simulation results are conducted to prove the practicability of the algorithm.
出处
《铁道通信信号》
2015年第4期17-20,共4页
Railway Signalling & Communication
基金
国家发改委
高速列车运行控制实验室建设项目之一
关键词
组合定位
联邦卡尔曼滤波
信息分配因子
Integrated positioning
Federated Kalman Filtering
Information sharing factors
