Multiple sensor fusion for 3D navigation for unmanned autonomous vehicles

Abstract

The paper presents a multiple sensor fusion for robust navigation based on Covariance Intersection (CI). The motivation of the approach described in this paper is a sensor based navigation with improved performance. The improved performance is quantified by explicit bounds of position estimate of the vehicle. The proposed algorithm results in 3D navigation and is based on the data fusion of the position and the orientation of the vehicle obtained from two different sources of sensor systems. Combining the measurements from different sources compensates for each other's limitations. Therefore the resulting performance of the sensor system is much improved than the individual sensor system.