Research on Combined Location Method of Dual Rail Inspection Vehicle Based on Adaptive Kalman Filter

Abstract

Abstract Dual rail inspection vehicle has the function of inspecting rail defect points automatically and an odometer is required for its localization. Since real-time localization of rail defect points still needs manual calibration, it cannot meet the requirements of automatic vehicle operation. In this paper, the automatic localization methods are discussed. The Adaptive Kalman Filter (AKF) is employed for the multi-sensor data fusion of the odometer and the Global Navigation Satellite System (GNSS). Then the GNSS/odometer combined localization model has been built to improve the accuracy and reliability of the inspection vehicle localization. In addition, the hardware board is designed. Finally, the on-line test has been performed on the Shanghai-Hangzhou railway line. The experimental results show that our combined localization method can significantly improve the accuracy compared with that of the single GNSS method from 1.848m to 1.093m.