Robust Estimation of UAV Dynamics in the Presence of Measurement Faults

Hacızade, Cengiz
Söken, Halil Ersin
This study introduces a robust Kalman filter (RKF) with a filter-gain correction for cases of measurement malfunctions. Using defined variables called measurement-noise scale factors, the faulty measurements are taken into consideration with a small weight and the estimations are corrected without affecting the characteristics of the accurate ones. In this study, RKF algorithms with single and multiple scale factors are proposed and applied for the state estimation process of an unmanned aerial vehicle (UAV) platform. The results of these algorithms are compared for different types of measurement faults, and recommendations for their utilization are given. DOI: 10.1061/(ASCE)AS.1943-5525.0000095. (C) 2012 American Society of Civil Engineers.


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This study discusses simultaneous adaptation of the process and measurement noise covariance matrixes for a nontraditional attitude filtering algorithm. The nontraditional attitude filtering algorithm integrates the singular value decomposition (SVD) method with the unscented Kalman filter (UKF) to estimate the attitude of a nanosatellite. The SVD method uses magnetometer and Sun sensor measurements as the first stage of the algorithm and estimates the attitude of the nanosatellite, giving one estimate at a...
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Söken, Halil Ersin (American Society of Civil Engineers (ASCE), 2013-07-01)
The unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for estimation problems of nonlinear systems even when high nonlinearity is in question. However, in the case of system uncertainty the UKF becomes inaccurate and diverges in time. In other words, if any change occurs in the process noise covariance, which is known a priori, the filter fails. This study introduces a novel adaptive fading UKF algorithm based on the correction of process noise covariance...
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Söken, Halil Ersin (American Society of Civil Engineers (ASCE), 2015-05-01)
Determining the process noise covariance of the unscented Kalman filter (UKF) is a difficult procedure. The analytical approximation method gives satisfactory results in certain cases, but it fails when generalized for the estimation of the extended states, such as the case that sensor biases or scale factors are included in the state vector. The main aim of this research is to find an appropriate tuning algorithm for the process noise covariance of the UKF when the magnetometer biases are estimated, as wel...
Citation Formats
C. Hacızade and H. E. Söken, “Robust Estimation of UAV Dynamics in the Presence of Measurement Faults,” JOURNAL OF AEROSPACE ENGINEERING, pp. 80–89, 2012, Accessed: 00, 2020. [Online]. Available: