Abstract

AbstractSmall unmanned aircraft systems (sUAS) have proven their effectiveness for measuring both the inertial and aircraft-relative wind. One of the more common aircraft-relative wind instruments is the multihole probe (MHP). While the MHP is accurate and simple to use, two main drawbacks exist: 1) the MHP airdata system can cost several times that of the sUAS and 2) the probe itself is often exposed to damage during routine operations. Flush airdata systems (FADS) are an alternative approach and utilize pressure ports flush with the aircraft surface. This removes any external components, thereby mitigating the risk of damage to the airdata system. The work presented details the implementation of a FADS for sUAS. Computational fluid dynamics simulations were used to determine the port locations of the FADS. Airframe locations were sorted based on the total sensitivity over a range of angles of attack and sideslip. The FADS was calibrated in flight using an onboard MHP. Multilayer feedforward neural networks were employed to produce estimates of the angle of attack and sideslip, while static and stagnation ports on the fuselage measured airspeed. Results from flight testing show errors in angle of attack and sideslip were unbiased. Additionally, 97.9% of the errors in airspeed were within 1 m s−1 of the MHP, while 93.8% and 87.3% of the angle of attack and sideslip errors, respectively, were within 1°. Flight tests show that a FADS can be calibrated in flight and that it is an effective method for measuring the aircraft-relative wind from small UAS.

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