Abstract
To improve the accuracy and reliability of the on‐board navigation system positioning, the positioning control algorithm of vehicle navigation system based on wireless tracking technology is proposed. By using modern information fusion technology, the accurate positioning of vehicle integrated navigation is realized, and the design goal of omnidirectional, all weather, and self‐contained positioning function is realized. Finally, the test shows that the accuracy and reliability of the positioning control algorithm of vehicle navigation system based on wireless tracking technology are improved than existing point system, speed measurement accuracy can reach 0.02 m/s, and positioning accuracy is about 18 meters. The vehicle operation efficiency and safety are greatly improved, and the traffic capacity is improved. And the traffic congestion is effectively alleviated, which provides reliable guarantee for the realization of traffic management automation and intelligent vehicle driving.
Highlights
With the acceleration of social development, there are many problems in road traffic in recent years, which makes intelligent transportation system get widespread attention
Using the zero lateral and celestial velocity of the vehicle during normal driving, the combined navigation filter measurement equation is obtained when the satellite signal fails; considering the difficulty to obtain the measured noise covariance matrix during the Kalman filtering, a new adaptive Kalman filtering (ADKF) algorithm is derived, which calculates the actual covariance of the new interest sequence, and adjusts the noise covariance matrix size using the fuzzy inference system (FIS) to adjust the noise covariance to navigate the vehicle position
This is because this paper designs a new algorithm based on loose combination and decentralized extended Kalman filtering, using a more detailed GPS coordinate conversion algorithm, replacing the traditional GPS localization scheme, and the software design integrates the secondary development of MapX map control, which significantly improves the positioning accuracy of the system
Summary
With the acceleration of social development, there are many problems in road traffic in recent years, which makes intelligent transportation system get widespread attention. Based on the equipment con3Duration of the current intelligent vehicle platform, the paper designs a new algorithm based on loose combination and decentralized extended Kalman filter, which makes full use of the complementary characteristics of GPS and inertial system in navigation and positioning information; second, in order to make the navigation and positioning of intelligent vehicles more accurate, a more detailed GPS coordinate conversion algorithm is adopted to replace the traditional GPS localization protocol used in the document [1], and the information preprocessing mechanism of GPS positioning system and inertial system is introduced; third, in order to realize the visualization effect of intelligent vehicle navigation and positioning, the software integrates the secondary development of MapX map control and draws the vehicle position and driving path in real time by using the dynamic layer principle and map matching algorithm; the above algorithm is tested in the intelligent vehicle platform [4]. Experiments demonstrate that the present design has higher system accuracy and reliability compared to existing literature methods
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