Abstract
Fixed and rotary-wing unmanned aircraft systems (UASs), originally developed for military purposes, have widely spread in scientific, civilian, commercial, and recreational applications. Among the most interesting and challenging aspects of small UAS technology are endurance enhancement and autonomous flight; i.e., mission management and control. This paper proposes a practical method for estimation of true and calibrated airspeed, Angle of Attack (AOA), and Angle of Sideslip (AOS) for small unmanned aerial vehicles (UAVs, up to 20 kg mass, 1200 ft altitude above ground level, and airspeed of up to 100 knots) or light aircraft, for which weight, size, cost, and power-consumption requirements do not allow solutions used in large airplanes (typically, arrays of multi-hole Pitot probes). The sensors used in this research were a static and dynamic pressure sensor (“micro-Pitot tube” MPX2010DP differential pressure sensor) and a 10 degrees of freedom (DoF) inertial measurement unit (IMU) for attitude determination. Kalman and complementary filtering were applied for measurement noise removal and data fusion, respectively, achieving global exponential stability of the estimation error. The methodology was tested using experimental data from a prototype of the devised sensor suite, in various indoor-acquisition campaigns and laboratory tests under controlled conditions. AOA and AOS estimates were validated via correlation between the AOA measured by the micro-Pitot and vertical accelerometer measurements, since lift force can be modeled as a linear function of AOA in normal flight. The results confirmed the validity of the proposed approach, which could have interesting applications in energy-harvesting techniques.
Highlights
Small unmanned aerial vehicles (UAVs), with maximum gross takeoff mass
This paper presented a kinematic model for estimation of airspeed, angle of attack α, and sideslip angle β for small UAVs equipped with low-cost, off-the-shelf commercial navigation sensors
The calibration technique used for the pressure sensor returned estimation errors of less than 3%
Summary
Few papers have considered practical methods for AOA and AOS estimation for small UAVs or light aircraft, due to the large weight, size, cost, and power consumption of the measuring devices. Estimates of these parameters can be used for fault detection and changes due to structural damage or adverse flight conditions that could alter the aerodynamic coefficients of a UAV, and could allow precise control of small UAVs in particular maneuvers, such as vertical landing [19] or high dynamic flight [20]. In low-level flight, typical for small UAVs, the turbulence intensity is significantly increased, due to the ground proximity [12], and wind estimation plays a crucial role in optimizing the onboard energy consumption, both for fixed-wing and rotary-wing aircraft. For low-level flights and small velocities (typical of small UAV mission scenarios), VCAS. can be assumed as equal to VTAS
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