TY - JOUR
T1 - In-Flight Estimation of Drag Parameters and Air Data for Unmanned Aircraft
AU - Ryu, Hanseok
AU - Lee, Changho
AU - Park, Youngmin
AU - Rhudy, Matthew B.
AU - Lee, Dongjin
AU - Jang, Dongjin
AU - Youn, Wonkeun
N1 - Publisher Copyright:
© 2022, AIAA International. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Identifying the drag parameters of unmanned aerial vehicles (UAVs) is crucial for guaranteeing their aerodynamic efficiency. However, in contrast to commercial aircraft, obtaining accurate UAV drag parameters is challenging because the existing approaches rely on analytical models or require accurate modeling of the engine thrust, which highly depends on time-varying wind conditions. To address this challenge, this paper first proposes a novel in-flight estimation algorithm for the air data (airspeed, angle of attack, and sideslip angle) and drag parameters of UAVs. With this approach, there is no need to compute all of the contributing components for drag, to model the thrust of the UAVs, or to perform complicated wind tunnel testing/computational fluid dynamics analysis to obtain the drag parameter. Instead, the proposed algorithm requires only standard sensors such as inertial measurement units and air data systems during gliding flight. Then, an efficient glide phase detection algorithm for initiating the filter is proposed. Simulation and experimental flight testing of a UAV demonstrate that the proposed algorithm yields accurate zero lift drag coefficient, attitude, and air data estimation results according to thorough validation with newly derived metrics for performance evaluation.
AB - Identifying the drag parameters of unmanned aerial vehicles (UAVs) is crucial for guaranteeing their aerodynamic efficiency. However, in contrast to commercial aircraft, obtaining accurate UAV drag parameters is challenging because the existing approaches rely on analytical models or require accurate modeling of the engine thrust, which highly depends on time-varying wind conditions. To address this challenge, this paper first proposes a novel in-flight estimation algorithm for the air data (airspeed, angle of attack, and sideslip angle) and drag parameters of UAVs. With this approach, there is no need to compute all of the contributing components for drag, to model the thrust of the UAVs, or to perform complicated wind tunnel testing/computational fluid dynamics analysis to obtain the drag parameter. Instead, the proposed algorithm requires only standard sensors such as inertial measurement units and air data systems during gliding flight. Then, an efficient glide phase detection algorithm for initiating the filter is proposed. Simulation and experimental flight testing of a UAV demonstrate that the proposed algorithm yields accurate zero lift drag coefficient, attitude, and air data estimation results according to thorough validation with newly derived metrics for performance evaluation.
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U2 - 10.2514/1.I010967
DO - 10.2514/1.I010967
M3 - Article
AN - SCOPUS:85125621109
SN - 1542-9423
VL - 19
SP - 166
EP - 178
JO - Journal of Aerospace Information Systems
JF - Journal of Aerospace Information Systems
IS - 3
ER -