TY - JOUR
T1 - Model-Aided State Estimation of HALE UAV with Synthetic AOA/SSA for Analytical Redundancy
AU - Youn, Wonkeun
AU - Choi, Hyoung Sik
AU - Ryu, Hyeok
AU - Kim, Sungyug
AU - Rhudy, Matthew B.
N1 - Funding Information:
Manuscript received February 24, 2020; accepted March 12, 2020. Date of publication March 16, 2020; date of current version June 18, 2020. This research was supported by a grant (20ACTO-B151661-02) from R&D Program funded by Ministry of Land, Infrastructure and Transport of Korean government. The associate editor coordinating the review of this article and approving it for publication was Dr. Amitava Chatterjee. (Corresponding author: Matthew B. Rhudy.) Wonkeun Youn, Hyoung Sik Choi, Hyeok Ryu, and Sungyug Kim are with the Unmanned Aircraft System Research Division, Aeronautics Research and Development Head Office, Korea Aerospace Research Institute, Daejeon 34133, South Korea (e-mail: wkyoun@kari.re.kr; chs@kari.re.kr; hryu@kari.re.kr; kkisy@kari.re.kr).
Publisher Copyright:
© 2001-2012 IEEE.
PY - 2020/7/15
Y1 - 2020/7/15
N2 - This paper proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of a high-altitude long-endurance (HALE) UAV without measurement of angle of attack (AOA) and sideslip angle (SSA). The major contribution of the proposed algorithm is that the synthetic AOA and SSA measurements are newly formulated for analytical redundancy. In the proposed filter, aerodynamic coefficients and control signals are utilized along with inertial measurement unit (IMU), Global Positioning System (GPS), and pitot tube measurements to estimate the navigation states as well as the steady and turbulent effects of 3D wind using random walk (RW) and Dryden wind models, respectively. Flight test results of a HALE UAV demonstrated that the proposed algorithm yields accurate estimated airspeed, AOA, SSA, attitude, angular rates, and 3D wind states, demonstrating its effectiveness for analytical redundancy.
AB - This paper proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of a high-altitude long-endurance (HALE) UAV without measurement of angle of attack (AOA) and sideslip angle (SSA). The major contribution of the proposed algorithm is that the synthetic AOA and SSA measurements are newly formulated for analytical redundancy. In the proposed filter, aerodynamic coefficients and control signals are utilized along with inertial measurement unit (IMU), Global Positioning System (GPS), and pitot tube measurements to estimate the navigation states as well as the steady and turbulent effects of 3D wind using random walk (RW) and Dryden wind models, respectively. Flight test results of a HALE UAV demonstrated that the proposed algorithm yields accurate estimated airspeed, AOA, SSA, attitude, angular rates, and 3D wind states, demonstrating its effectiveness for analytical redundancy.
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U2 - 10.1109/JSEN.2020.2981042
DO - 10.1109/JSEN.2020.2981042
M3 - Article
AN - SCOPUS:85088017878
VL - 20
SP - 7929
EP - 7940
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
IS - 14
M1 - 9037278
ER -