Unmanned vehicle state estimation fusing multi sensors using extended Kalman filter

Abstract

The potential is in unmanned vehicles (UV) for many military and civil applications such as logistics, surveillance and combating terrorism. The increase in the demand for UVs is due to decreasing prices of sensors and embedded systems. Using these sensors separately is not efficient since they don’t provide the complete data set or the required accuracy degree. Therefore multi sensors solution has to be sought to find a synergy between the sensors to overcome and compensate the drawbacks of individual sensors. A multi sensors solution is proposed, tested and validated to estimate the state of an unmanned vehicle. The solution is based on the fusion of the sensors by Extended Kalman Filter. The proposed solution proved its superiority over stand alone sensor solutions.

Date of Award	2013
Original language	American English
Supervisor	Seneviratne Seneviratne (Supervisor)