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Synthetic Air Data Systems: Using Sensor Fusion to Estimate Air Data Parameters

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Abstract

Synthetic air data systems generate estimates of angle of attack, side slip and/or airspeed which are key parameters required to ensure that an airplane is operating safely within its flight envelope.  Unlike traditional air data system which rely on vanes, pressure, and temperate measurements to determine these quantities, synthetic systems rely on sensor fusion approaches to estimate these parameters.  They generate the air data parameter estimates by fusing information from GPS/GNSS, inertial measurement units and/or the equations of motion of an airplane.   This presentation discusses system architectures for synthetic air data estimation and analyzes the tradeoff involved in the different system architectures.  System architectures whereby a synthetic system can be used for fault detection of traditional air data systems is also discussed.  Simulation and experimental results from Unmanned Aerial Vehicle (UAV) flight tests showing the performance of synthetic air data filters will be presented.