GPS aided Extended Kalman Filter based localization for unmanned vehicles

Abstract

This paper presents design considerations of a GPS-aided localization system for unmanned vehicles used in outdoor applications. The system proposed in this paper is based on Extended Kalman Filter (EKF) and also integrates Global Positioning System (GPS) measurements. Localization and navigation systems are base components of all unmanned vehicles since they give unmanned vehicles the ability of perceiving the environment in order to localize themselves and to navigate to a target. The advantage of the proposed system over a GPS based localization system is that the system works even if the GPS receiver does not receive any GPS signals. In this study, firstly proposed EKF-based localization system is explained, and then how to integrate GPS measurements into this localization system is explained. With simulation studies in MATLAB, the effectiveness of the system is shown. The simulations show that the proposed localization system gives accurate results with negligible positional errors.