Sensor Fault Detection for UAVs using a Nonlinear Dynamic Model and the IMM-UKF Algorithm
Cork, Lennon R. & Walker, Rodney A. (2007) Sensor Fault Detection for UAVs using a Nonlinear Dynamic Model and the IMM-UKF Algorithm. In 2007 Information Decision and Control (IDC), 12 Feb - 14 Feb, Adelaide, Australia.
This paper presents a method of Fault Detection, Identification and Accommodation for inertial sensors in Unmanned Aerial Vehicles. A nonlinear model of the aircraft’s dynamics replace the traditional inertial navigation equations and is used in conjunction with the Interacting Multiple Model and the Unscented Kalman Filter for improving state estimation in presence of inertial sensor faults. Performance comparisons are made between filters using the inertial navigation equations and the dynamic model for the fault-free conditions. It is shown that a matched UKF will result in adequate state estimation regardless of the failure mode and that the IMM-UKF algorithm is a step closer to achieving the same performance. The IMM-UKF is shown capable of maintaining stable state estimates in the presence of all single inertial sensor faults.
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|Item Type:||Conference Paper|
|Keywords:||IMM, UKF, Aerodynamic Model|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerospace Engineering not elsewhere classified (090199)|
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
|Copyright Owner:||Copyright 2007 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||08 Jun 2007|
|Last Modified:||29 Feb 2012 13:41|
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