Research On Vehicle Three-Dimensional Positioning Based On Coordinate Transformation Algorithm

With the further construction and expansion of the road network,complex three-dimensional road conditions are increasing.Due to the large error of the vehicle height information provided by the general positioning system,when the vehicle encounters a relatively complicated three-dimensional scene,it will has positioning error and incorrect navigation information.This paper studies the positioning problem of vehicles using the global navigation satellite system to improve positioning accuracy under three-dimensional road conditions.The specific work and research results are as follows.(1)Aiming at the problem that the vehicle’s height measurement error is too large under complex three-dimensional road conditions,The vehicle spatial positioning method is improved based on the motion of the vehicle on a two-dimensional plane or curved surface.Considering that the positioning problem of the three-dimensional space is transferred back to the two-dimensional plane,and use estimated position information in the plane to solve height information,thereby positioning accuracy can be improved.The three-dimensional GIS is used to assist the vehicle positioning,and the phenomenon that the vehicle is on the bridge or under the bridge and suspended on the ground in the navigation system is effectively improved.(2)The positioning accuracy of the vehicle in the two-dimensional plane is further improved.Since the observed noise variance is susceptible to environmental interference,the fuzzy control theory is introduced in the Cubature Kalman Filtering algorithm to correct the observed noise variance.Under the nonlinear motion model,when the state parameter of the vehicle changes,the positioning error increases.To this end,the paper combines the Cubature Kalman Filtering algorithm based on distributed fuzzy control with the Interacting Multiple Model algorithm.From the simulated overpass scenarios,we can see that compared with the Cubature Kalman Filtering algorithm based on distributed fuzzy control,the overall positioning accuracy of the improved algorithm can be increased by about 35%.The research of this paper can provide a reference for the vehicle positioning in the complex three-dimensional path,and how to determine the position and speed of the vehicle in the intelligent transportation system.