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

A novel sensor fusion design framework is presented with the objective of improving the overall multi-sensor 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. This work was supported in part by NASA under project numbers: NNX10AI14G and NNX12AM56A. Dr. Yu Gu is an Assistant Professor within the Department of Mechanical and Aerospace Engineering (MAE) at West Virginia University (WVU), Morgantown , WV 26506 USA (304-293-3992; fax: 304-293-6689; e-mail: Yu.Gu (at) mail.wvu.edu). Dr. Jason N. Gross is an Assistant Professor within the MAE Department at WVU, Morgantown, WV 26506 USA (e-mail: Jason.Gross (at) mail.wvu.edu). Dr. Matthew B. Rhudy is an Assistant Professor within the Division of Engineering, Pennsylvania State University, Reading, PA, 19610, USA, (matthew.rhudy (at) gmail.com). Kyle Lassak is a Ph.D. candidate at the MAE Department at WVU, Morgantown, WV 26506 USA (e-mail: klassak (at) mix.wvu.edu). Yu Gu, Jason N. Gross, Matthew B. Rhudy, Kyle Lassak A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation