Flight Parameter Detection via a Pressure-Velocity Fusion Algorithm with a Flexible Sensing Patch
Precise measurement of flight parameters—including angle of attack (AOA), angle of sideslip (AOS), and airspeed—is critical for stabilized control of unmanned aerial vehicles (UAVs) in complex aerodynamic environments. Conventional rigid sensors fail to conform to curved leading edges, disrupting local flow and degrading aerodynamic performance, and are ill-suited for UAV miniaturization. Emerging flexible sensing technologies using hot-film, piezoresistive, or capacitive transduction offer potential solutions. This work presents a flexible pressure-velocity sensing patch developed by Professor Jiang's team at Beihang University. The patch integrates a capacitive differential pressure sensor array and a vector flow sensor, fabricated via a multi-layer polyimide bonding process. The capacitive differential pressure sensor features dual-layer chambers, achieving a resolution of 12 mPa within 0–1 Pa, superior to traditional single-layer designs. The vector flow sensor operates on the calorimetric principle, using a micro-heater and thermistor array to characterize flow velocity and direction. A novel pressure-velocity fusion (PVF) algorithm introduces spanwise velocity (Vz) to decouple AOA and AOS, reducing computational complexity compared to classic three-sensor algorithms. Computational fluid dynamics (CFD) simulations validated the algorithm's reliability under wind tunnel conditions. The sensing patch enables simultaneous measurement of multiple flight parameters with high precision and low computational cost, addressing the limitations of rigid sensors and advancing UAV aerodynamic sensing.