Application Research of Cubature Kalman Filter in Vehicle Positioning

In the era of the Internet of Everything, accurate vehicle location information in the transportation system is particularly important. In order to obtain accurate vehicle position, after acquiring basic data through GPS or other hardware collection, a series of data processing can be performed, which can improve the accuracy of vehicle positioning to a certain extent. In this paper, Cubature Kalman Filter (CKF) algorithm is used to predict the position of the vehicle through the model and then fuse the collected data to improve the accuracy of vehicle position. And the combination of adaptive Interactive Multi-mode algorithm and Cubature Kalman Filter algorithm can adapt to various maneuvering states of vehicles. Simulation experiments show that the positioning accuracy of the Interactive Multi-mode Cubature Kalman Filter (Imm-CKF) algorithm can be improved by about 20% compared to the Cubature Kalman Filter algorithm.