Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

Wonkeun Youn; Hyoungsik Choi; Am Cho; Sungyug Kim; Matthew B. Rhudy

doi:10.1109/TAES.2020.2988962

Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

Wonkeun Youn, Hyoungsik Choi, Am Cho, Sungyug Kim, Matthew B. Rhudy

Division of Engineering, Business & Computing (Berks)

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.

Original language	English (US)
Article number	9076038
Pages (from-to)	4300-4314
Number of pages	15
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	56
Issue number	6
DOIs	https://doi.org/10.1109/TAES.2020.2988962
State	Published - Dec 2020

All Science Journal Classification (ASJC) codes

Aerospace Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/TAES.2020.2988962

Cite this

@article{8d9e182ea0a14c74bebc6f7b11d236a6,

title = "Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV",

abstract = "This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.",

author = "Wonkeun Youn and Hyoungsik Choi and Am Cho and Sungyug Kim and Rhudy, {Matthew B.}",

note = "Funding Information: This work was supported by the Core Technologies of Electric Vertical Take-Off & Landing Aircraft (FR20A00) through the National Research Council of Science & Technology. Publisher Copyright: {\textcopyright} 1965-2011 IEEE.",

year = "2020",

month = dec,

doi = "10.1109/TAES.2020.2988962",

language = "English (US)",

volume = "56",

pages = "4300--4314",

journal = "IEEE Transactions on Aerospace and Electronic Systems",

issn = "0018-9251",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "6",

}

TY - JOUR

T1 - Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

AU - Youn, Wonkeun

AU - Choi, Hyoungsik

AU - Cho, Am

AU - Kim, Sungyug

AU - Rhudy, Matthew B.

N1 - Funding Information: This work was supported by the Core Technologies of Electric Vertical Take-Off & Landing Aircraft (FR20A00) through the National Research Council of Science & Technology. Publisher Copyright: © 1965-2011 IEEE.

PY - 2020/12

Y1 - 2020/12

N2 - This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.

AB - This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.

UR - http://www.scopus.com/inward/record.url?scp=85094148559&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85094148559&partnerID=8YFLogxK

U2 - 10.1109/TAES.2020.2988962

DO - 10.1109/TAES.2020.2988962

M3 - Article

AN - SCOPUS:85094148559

SN - 0018-9251

VL - 56

SP - 4300

EP - 4314

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

IS - 6

M1 - 9076038

ER -

Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this