a fault-tolerant multiple sensor fusion approach applied to uav attitude estimation

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ID: 249363
2016
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Abstract
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.
Reference Key
gu2016internationala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Yu Gu;Jason N. Gross;Matthew B. Rhudy;Kyle Lassak
Journal shanghai kou qiang yi xue = shanghai journal of stomatology
Year 2016
DOI
10.1155/2016/6217428
URL
http://dx.doi.org/10.1155/2016/6217428
Keywords
motor vehicles astronautics aeronautics

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