Haiyang Chao, University of Kansas

Angle of attack (AOA) and angle of sideslip (AOS) describe the interaction between flight vehicles and the surrounding air, which have significant influences on aircraft aerodynamics. This talk focuses on the design, implementation, and evaluation of four filters for the estimation of angle of attack (AOA) and angle of sideslip (AOS) of small unmanned aerial vehicles (UAVs). Specifically, two novel filters (a complementary filter and an extended Kalman filter) are proposed and evaluated without using direct flow angle and GPS measurements; two existing AOA/AOS filters are also implemented and evaluated. All filters are designed with minimal inputs and states to ensure the ease of implementation, simplicity of tuning, and computation efficiency. Both simulation and UAV flight test results show the performance of the proposed filters. Especially, flight test results from two different UAVs (a T-tail UAV and a flying wing UAV) show that the root mean square errors of estimated inertial AOA and AOS are less than 1.5 degrees under nominal flight conditions and around 2 degrees under aggressive maneuvers compared with direct flow angle measurements.