The increasing population density in metropolitan areas, coupled with the faster pace of everyday life, calls for the development of Inter-Urban Air Mobility (UAM) solutions. Currently, there is a gap in the market since there is no competitor that can facilitate all market segments and also provide “last-mile transport” by air. This report aims to identify a promising Inter-UAM design, the Swing, focused on minimising the aircraft’s ground and environmental footprint. The small ground footprint will enable the vehicle to take off from smaller vertiports, helipads or even driveways, allowing it to penetrate urban areas and land where other UAM vehicles cannot.

Pitot tube-free airspeed estimation methods exist for fixed-wing and multirotor configurations, but lack direct applicability to hybrid unmanned air vehicles due to their wide flight envelope and changing dynamics during transition. This work proposes a novel synthetic air data system for the Variable Skew Quad Plane (VSQP) hybrid vehicle to allow airspeed estimation from hover to high speed forward flight and provide pitot tube fault detection. An Extended Kalman Filter fuses Global Navigation Satellite System (GNSS) and inertial measurements using model-independent kinematics equations to estimate wind and airspeed without the use of the pitot tube. The filter is augmented by a simplified vehicle force model. Pitot tube fault detection is achieved with a simple thresholding operation on the pitot tube measurement and the airspeed estimation residual. Accurate airspeed estimation was validated with logged test flight data, achieving an overall 1.62 m/s root mean square error. Using the airspeed estimation, quick detection (0.16 s) of a real-life abrupt pitot tube fault was demonstrated. This new airspeed estimation method provides an innovative approach for increasing the fault tolerance of the VSQP and similar quad-plane vehicles.