Research On High Precision Satellite Positioning Algorithm For Vehicle Monitoring

With the development of the Beidou navigation satellite system,during the Beidou positioning monitoring process,the “two passengers and one danger”operating vehicle often caused positional drift due to factors such as building blockage,other positioning signal interference and bad weather,resulting in a decrease in positioning accuracy.Affecting the normal development of the business vehicle business.Therefore,studying the high-precision Beidou positioning algorithm is of great significance for promoting the development of the business.In order to reduce the accidental error generated in the satellite positioning process and improve the positioning accuracy and anti-interference of vehicle positioning,this thesis proposes an adaptive Kalman filtering positioning algorithm based on Kalman filtering algorithm.By optimizing the positioning model,improving the filtering accuracy and convergence speed,the random error occurring in the Beidou positioning is corrected and compensated,which improves the accuracy and reliability of the algorithm.Using MATLAB simulation tools for simulation verification,the accuracy can be improved compared to other algorithms.In addition,for the long-term interference of Beidou signal,the error caused by the accumulation of dead reckoning is not corrected and increased.An improved map positioning trajectory matching framework is proposed to automatically identify the trajectory generated from the user and update the geospatial map.Since road tracking is sparse and noisy,the improved framework validates the user's map changes before the user posts the map.Compared with the traditional method,the proposed framework achieves up to four times the map matching performance with a loss of accuracy of only 0.1-0.3%.