Search

The virtual air data sensor leverages smartphone-grade inertial and GPS sensors with advanced computational methods to generate accurate air flow data in real time. The innovation uses inexpensive sensors typically present on smartphones, along with real-time modeling, filtering, and data reconstruction using kinematic equations. Operating within the aircraft fuselage, the algorithm avoids environmental exposure and flow field complications affecting traditional external sensors. The algorithm employs a dual-methodology approach for real-time air flow estimation. It calibrates an aerodynamic model during calm air conditions, using aircraft response characteristics to compute air flow angles from vertical and lateral acceleration data through frequency-domain modeling. Simultaneously, kinematic relationships with GPS-corrected sensor bias estimation reconstruct independent air flow data at lower update rates. Advanced complementary filtering blends these streams to generate continuous airspeed, angle of attack, and sideslip angle measurements. The algorithm incorporates automated calibration, vertical acceleration-based alpha estimation, and GPS-based low-frequency angle reconstruction using kinematic expressions. The innovative algorithm is self-calibrating and provides independent, reliable, and accurate virtual sensing that can be implemented with readily-available hardware. The technology is currently TRL 5 (component validated in relevant environment) and available for licensing.