Position estimation using extended Kalman Filter and RTS-smoother in a GPS receiver

摘要

This article presents an alternative approach of position estimation in a GPS software receiver, making use of extended Kalman Filter and Rauch-Tung-Striebel-smoother (RTS-smoother). Applications of both Least-Squares Method (LSM) and Extended Kalman Filter (EKF) in GPS position estimation are included and compared. Experimental results show that EKF gives a more accurate and stable estimation than LSM does. Furthermore, significant improvement in position precision and accuracy can be seen when the TRS-smoother is applied to the EKF model.