Accelerometer Fault-Tolerant Model-Aided State Estimation for High-Altitude Long Endurance UAV

This article proposes a novel fault-Tolerant dynamic model-Aided navigation filter to cope with accelerometer faults. An algorithm to estimate the three-Axis accelerations of a high-Altitude long-endurance (HALE) unmanned aerial vehicle (UAV) utilizing control input signals and aerodynamic coefficient parameters is newly proposed. To address the fault of the accelerometer, two model-Aided navigation filters that utilize the measured acceleration, denoted as Acc-measure algorithm, and estimated acceleration, denoted as Acc-free algorithm, respectively, are effectively combined under the interacting multiple model (IMM) framework to integrate the optimality of Acc-measure algorithm and robustness of Acc-free algorithm. Flight test results demonstrated that the proposed algorithm yields robust attitude and wind estimation results in the presence of different types of accelerometer faults compared with Acc-measure and Acc-free algorithms while accurately detecting the fault of the accelerometer.

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Work Title Accelerometer Fault-Tolerant Model-Aided State Estimation for High-Altitude Long Endurance UAV
Open Access
  1. Wonkeun Youn
  2. Hyoungsik Choi
  3. Am Cho
  4. Sungyug Kim
  5. Matthew B. Rhudy
License In Copyright (Rights Reserved)
Work Type Article
  1. Institute of Electrical and Electronics Engineers (IEEE)
Publication Date 2020
Publisher Identifier (DOI)
  1. 10.1109/tim.2020.2988748
  1. IEEE Transactions on Instrumentation and Measurement
Deposited September 09, 2021




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Work History

Version 1

  • Created
  • Added M Rhudy - Accelerometer Fault-Tolerant.pdf
  • Added Creator Wonkeun Youn
  • Added Creator Hyoungsik Choi
  • Added Creator Am Cho
  • Added Creator Sungyug Kim
  • Added Creator Matthew B. Rhudy
  • Published
  • Updated
  • Updated