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Mathematical Problems in Engineering
Volume 2013, Article ID 819565, 11 pages
Research Article

A Novel Fusion Scheme for Vision Aided Inertial Navigation of Aerial Vehicles

College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China

Received 17 April 2013; Revised 12 August 2013; Accepted 19 August 2013

Academic Editor: Rafael Martinez-Guerra

Copyright © 2013 Ming Xiao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Vision-aided inertial navigation is an important and practical mode of integrated navigation for aerial vehicles. In this paper, a novel fusion scheme is proposed and developed by using the information from inertial navigation system (INS) and vision matching subsystem. This scheme is different from the conventional Kalman filter (CKF); CKF treats these two information sources equally even though vision-aided navigation is linked to uncertainty and inaccuracy. Eventually, by concentrating on reliability of vision matching, the fusion scheme of integrated navigation is upgraded. Not only matching positions are used, but also their reliable extents are considered. Moreover, a fusion algorithm is designed and proved to be the optimal as it minimizes the variance in terms of mean square error estimation. Simulations are carried out to validate the effectiveness of this novel navigation fusion scheme. Results show the new fusion scheme outperforms CKF and adaptive Kalman filter (AKF) in vision/INS estimation under given scenarios and specifications.