Novel Approach to Position and Orientation Estimation in Vision-Based UAV Navigation

Author

Zhang, J. ; Wu, Y. ; Liu, W. ; Chen, X.

Author_Institution

Univ. of Wisconsin-Milwaukee, Milwaukee, WI, USA

Volume

46

Issue

2

fYear

2010

fDate

4/1/2010 12:00:00 AM

Firstpage

687

Lastpage

700

Abstract

A novel approach to position and orientation estimation for vision-based UAV (unmanned aerial vehicle) navigation is described. In this approach the position and orientation estimation problem is formulated as a tracking problem and solved by using an extended Kalman filter (EKF). The state and observation models of the EKF are established based on an analysis of the imaging geometry of the UAV´s video camera in connection with a DEM (digital elevation map) of the area of flight, which helps to control estimation error accumulation. The efficacy of our approach is demonstrated by simulation experiment results.

Keywords

Kalman filters; aircraft control; image sensors; path planning; remotely operated vehicles; robot vision; UAV video camera; control estimation error; digital elevation map; extended Kalman filter; orientation estimation; position estimation; unmanned aerial vehicle; vision-based UAV navigation; Aircraft navigation; Airplanes; Cameras; Computer science; Estimation error; Geometry; Global Positioning System; Reconnaissance; Solid modeling; Unmanned aerial vehicles;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2010.5461649

Filename

5461649