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International Journal of Aerospace Engineering
Volume 2016 (2016), Article ID 6217428, 12 pages
Research Article

A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation

1Department of Mechanical and Aerospace Engineering (MAE) at West Virginia University (WVU), Morgantown, WV 26506, USA
2Division of Engineering, Pennsylvania State University, Reading, PA 19610, USA

Received 1 October 2015; Revised 15 January 2016; Accepted 27 January 2016

Academic Editor: Enrico C. Lorenzini

Copyright © 2016 Yu Gu 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.


A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF) is used to provide a useful tool for combining information from multiple sources. A two-step off-line and on-line calibration procedure refines sensor error models and improves the measurement performance. A Fault Detection and Identification (FDI) scheme crosschecks sensor measurements and simultaneously monitors sensor biases. Low-quality or faulty sensor readings are then rejected from the final sensor fusion process. The attitude estimation problem is used as a case study for the multiple sensor fusion algorithm design, with information provided by a set of low-cost rate gyroscopes, accelerometers, magnetometers, and a single-frequency GPS receiver’s position and velocity solution. Flight data collected with an Unmanned Aerial Vehicle (UAV) research test bed verifies the sensor fusion, adaptation, and fault-tolerance capabilities of the designed sensor fusion algorithm.