Unscented Kalman filter for GPS based positioning and tracking services

Abstract

In the present world, GPS requirement is increasing in almost every field for different applications. One of the major applications is GPS receiver positioning in defense and civilian applications like online transportation tracking status, tracking location of senior citizens, school kids and in different types of surveying applications etc. GPS positioning is a nonlinear process. Received GPS signal is corrupted by noise and hence the extraction of original signal from corrupted signal is the main task. The implementation of adaptive filters for such type of non linear estimation problems provides better results. In this paper, position of a GPS receiver is estimated by Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF). Required data is taken from GPS navigation and observation Files. The estimated position is compared with surveyed receiver position coordinates, along with receiver clock error. The results show that Unscented Kalman Filter (UKF) provides better positioning with less time of convergence compared to EKF. Thus, Unscented Kalman Filter (UKF) is fast and accurate for estimation of GPS receiver position and also for nonlinear system applications.