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

Ming Xiao,Liang Pan,Lincheng Shen,Tianjiang Hu

doi:10.1155/2013/819565

Ming Xiao, Liang Pan + Show 2 more

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https://doi.org/10.1155/2013/819565

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Abstract

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.

Highlights

Over the past decade, aerial vehicles have been widely developed and used in military and civilian cases, such as reconnaissance, surveying, mapping, and geophysical exploration [1]
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 even though vision-aided navigation is linked to uncertainty and inaccuracy
Several navigation frameworks aided by global positioning system (GPS) [1, 5], vision [1, 6,7,8,9,10], or terrain [11, 12] are usually employed to restrict the growth of Inertial navigation system (INS) error

Summary

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. Vision-aided inertial navigation is an important and practical mode of integrated navigation for aerial vehicles. 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 even though vision-aided navigation is linked to uncertainty and inaccuracy. By concentrating on reliability of vision matching, the fusion scheme of integrated navigation is upgraded. Results show the new fusion scheme outperforms CKF and adaptive Kalman filter (AKF) in vision/INS estimation under given scenarios and specifications

Introduction

Novel Fusion Scheme for Vision-Aided Navigation

Simulation and Discussion

Conclusions