Model-Aided Synthetic Airspeed Estimation of UAVs for Analytical Redundancy

This letter proposes a novel method for model-aided synthetic airspeed estimation of UAVs. The major contribution of the proposed algorithm is that the synthetic airspeed measurement is newly formulated for analytical redundancy. This filter only requires inertial measurement unit (IMU), airflow angles, and elevator control input along with a simple aircraft model containing only three lift coefficient parameters; no GPS or complex aircraft dynamic model are required. Particularly, two novel filters (unscented Kalman filter and complementary filter) are proposed and evaluated without direct airspeed and GPS measurements. Flight test results of a UAV demonstrated that the proposed algorithm yields accurate estimated airspeed, demonstrating its effectiveness for analytical redundancy.

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Work Title Model-Aided Synthetic Airspeed Estimation of UAVs for Analytical Redundancy
Open Access
  1. Wonkeun Youn
  2. Hanseok Ryu
  3. Dongjin Jang
  4. Changho Lee
  5. Youngmin Park
  6. Dongjin Lee
  7. Matthew B. Rhudy
License In Copyright (Rights Reserved)
Work Type Article
  1. IEEE Robotics and Automation Letters
Publication Date June 4, 2021
Publisher Identifier (DOI)
Deposited November 12, 2021




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Work History

Version 1

  • Created
  • Added Model_Aided_Synthetic_Airspeed_Estimation_of_UAV_for_Analytical_Redundancy-1.pdf
  • Added Creator Wonkeun Youn
  • Added Creator Hanseok Ryu
  • Added Creator Dongjin Jang
  • Added Creator Changho Lee
  • Added Creator Youngmin Park
  • Added Creator Dongjin Lee
  • Added Creator Matthew B. Rhudy
  • Published
  • Updated
  • Updated
  • Updated