GPS-denied navigation using location estimation and texel image correction

Abstract

This paper presents a localization system for Unmanned Aerial Vehicles (UAVs), specifically designed for small UAVs to be used in a GPS-denied local area by using estimation algorithms incorporating camera and Light Detection and Ranging (LiDAR) sensor fusion. Localization techniques classically rely on Global Positioning System (GPS) information. However, GPS is subject to jamming. This paper proposes methods of localization without reliance on the GPS. This system utilizes Error-State Extended Kalman Filtering (ESEKF) and methods of camera to LiDAR sensor fusion to correct for error propagations in the aerial vehicle's estimated location.Initial results from the GPS-denied navigation method showed that the location of the sUAV to an average error of 3.2 m was possible using only texel images and velocity measurements from an experimental flight.