An Advanced Unscented Kalman Filter and Fuzzy-Based Approach for GPS Position Estimation Real-Time Applications

Abstract

Currently, the necessity for GPS is evolved in each stage throughout several applications, due to the increasing number of applications related to GPS, the need for GPS receiver positioning is increasing in almost every field. This process is a bit like a nonlinear process. To get the exact position of the GPS receiver, the received signal is corrupted due to the many factors that must be rectified. Also, the error of satellite orbit is very important to determine the exact position of GPS device. These errors are minimized statistical signal processing and Adaptative filtering techniques are commonly applied to estimate the GPS receiver position. In this work, estimation of the receiver position is done through the Extended Kalman filter (EKF). The result of this study projects the efficiency of the Unscented Kalman filter (UKF) method which is better than EKF in tracking the GPS receiver position than the EKF.