基于GNSS与IMU的现代有轨电车组合定位方法研究

摘要

The navigation system composed of the combination of GNSS and IMU has the advantages of all-weather, day time, high dynamic and no error accumulation with time. Combined with modern tram positioning characteristics, the paper proposed a combined positioning method based on GNSS and IMU. The method utilize the two sensors of GNSS and IMU placed at different locations to collect data. A fusion algorithm was proposed in the light of a new voting mechanism, which can compromise the merits of fuzzy decision for the complete data fusion of multi-sensors (IMU) and reduce the random error. The failure criterion was put forward after the analysis of the fault diagnosis and isolation methods of the GNNS, and the optimal fusion and fault tolerant processing of the data of GNNS and IMU were realized by the application of the Federal adaptive Kalman filter algorithm. Analysis showed that: This design can achieve high precision and reliable positioning. Compared with the traditional GNSS and IMU positioning, the positioning accuracy is reduced by 40.2％, and the failure tolerance gains further improvements.%GNSS与IMU组合导航系统具有全天候、全天时、高动态和误差不随时间积累的优点,结合现代有轨电车定位需求,提出一种基于GNSS与IMU的现代有轨电车组合定位方法.该方法利用GNSS和IMU 2种传感器安装在不同位置来实现数据采集,基于模糊投票机制决策的融合算法,能够实现对多IMU传感器的数据融合,减小随机误差;分析GNSS系统的故障诊断与隔离方法,给出故障判别条件;提出采用自适应联邦卡尔曼滤波算法实现GNSS与IMU数据最优融合和可容错处理.研究结果表明:本方案能够实现高精度可靠定位,与传统的GPS与IMU组合定位相比,其定位精度提高了40.2％,系统的容错能力得到进一步提高.