Self-Calibrating Virtual Sensor

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. Air flow measurement systems are widely used for flight instrumentation and aviation safety, yet their application to real-time aircraft operation presents unique challenges due to local flow field distortions, calibration complexities, and sensor positioning constraints. Achieving desired measurement accuracy, reliability across flight regimes, and environmental resilience is difficult within conventional aircraft sensor systems, as these parameters depend on sensor placement, calibration procedures, and proximity to aircraft structures. This restricts accessibility of critical flight data and increases instrumentation costs in general aviation and automated flight systems. Current approaches require expensive external hardware subject to flow distortions near fuselage and wings, creating calibration difficulties and reliability concerns that barrier widespread implementation of affordable, accurate systems essential for flight safety. To address these limitations, researchers at NASA Langley Research Center developed a self-calibrating virtual sensor. This solution applies to general aviation aircraft, UAVs, and experimental aircraft requiring cost-effective air flow measurement.