Research On Vehicle Speed Measurement And Positioning Technology Based On Multi-source Information Fusion

In recent years,with the continuous growth of car ownership and the development of information technology,vehicle-borne navigation systems have played a key role in promoting the development of ITS and multi-field collaborative applications.However,due to the complexity of urban roads and the unavailability of satellite navigation in special areas,the single navigation system can not locate in a complex environment.Therefore,vehicle-borne position technology based on multi-source information fusion has become the development direction of the navigation field.Two typical applications in vehicle speed measurement and position technology based on multi-source information fusion: one applies to map matching technology applied in the civil field to promote road network construction and smart city development;the other applies to the autonomous integrated navigation technology applied in the military field and aerospace field to improve the concealment and autonomy of vehicles and ensure the positioning accuracy.Therefore,according to needs in the vehicle speed measurement and positioning with or without satellite signal,this paper adopts spatial-temporal analysis and integrated navigation method to focus on the vehicle speed measurement and positioning algorithm which is based on multisource information fusion technology.The main research content are as follows:1.Preprocessing and analysis GPS trajectories and the road network,including the redundant data and outlier data,are eliminated,the topological structure of the road network is constructed and the road network data is divided by grid.Establishing the mapping relationship between GPS trajectories,grid and roads,the candidate set of road sections are filtered by error region,the eigenvalues of GPS trajectories are calculated.2.Considering the requirements of vehicle trajectory positioning needs in low frequency satellite signal,an offline map matching system is built.Based on the spatialtemporal analysis,the candidate links are scored by the distance,heading,connectivity and speed limit of the road network,which the optimal matching path is identified.and the algorithm efficiency is improved by adopting segment matching.3.An autonomous integrated navigation scheme of inertial navigation system(INS)/laser Doppler velocimeter(LDV)is designed in order to autonomously measure the speed and position of the military vehicular and flying train without the satellite signal.Considering the mathematical model relative to LDV.the error model of integrated navigation is deduced and verified by simulation.4.Based on the working characteristics of INS and LDV,the original prototype of integrated navigation is developed.The scale factor error and installation error of LDV,the problem of repeated calibration of system parameters and the stability and reliability are improved.The map matching experiments are performed on GPS trajectory data.The results show the accuracy of the algorithm in low frequency signal.The positioning and speed measurement function of the integrated navigation prototype is tested by the dynamic vehicle experiment,and the results demonstrate the original prototype’s antidisturbance and positioning accuracy.Meanwhile,which is conducive to developing the engineering prototype.