Multi-sensor fusion method using kalman filter to improve localization accuracy based on android smart phone

Abstract

Android smart phone can be used in ITS (Intelligent Transportation Systems) to obtain people and vehicle's location since it is integrated with GPS, direction sensor and acceleration sensor. Because the GPS built in smart phone always has an error of dozens of meters, improving the positioning accuracy is necessary before introducing it into ITS. This paper proposed an approach to improve the accuracy to the street level and get a smooth trajectory without jump points. It is convenient for everyone to use it because almost everyone has a smart phone. Firstly, road-matching algorithm is used to improve the localization accuracy to street level; secondly, speed and direction information are introduced to better reflect the real trajectory; thirdly, Kalman filter is used to eliminate the jump points and make the trajectory smooth; finally, the optimal result obtained from the process of Kalman filter is interpolated to reflect more details. The experiment result shows that the approach is effective.