Abstract: Due to cost and energy consumption limitations, there are significant differences in the positioning capabilities of mobile terminals, resulting in unsatisfactory quality of trajectory data. In this paper, satellite Doppler data is used to optimize trajectory data. First, the system state equation is established by the kinematic relationship between the measured velocity and position, and the static linear Kalman filter estimates the optimal system state. Then a dynamic Kalman filter system is established by correlating the measurement error matrix parameters of the Kalman filter with the vertical dilution of precision of satellite positioning. Finally, the whole-day trajectory of a taxi in Shenzhen was visualized, and the deviation between the trajectory points and the urban road was calculated to compare the optimized and non-optimized taxi trajectories. The results show that the proposed optimization method can effectively reduce the deviation between trajectory points and urban roads, and this method can be used to process vehicle trajectory data in urban traffic research.

Junzhuo Li, Wenyong Li and Guan Lian. “Optimization Method for Trajectory Data Based on Satellite Doppler Velocimetry”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.9 (2023). http://dx.doi.org/10.14569/IJACSA.2023.0140908

@article{Li2023,
title = {Optimization Method for Trajectory Data Based on Satellite Doppler Velocimetry},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140908},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140908},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {9},
author = {Junzhuo Li and Wenyong Li and Guan Lian}
}