Nontraditional Attitude Filtering with Simultaneous Process and Measurement Covariance Adaptation

Hacızade, Cengiz
Söken, Halil Ersin
Cilden-Guler, Demet
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 single frame. Then these estimated attitude terms are used as input to an adaptive UKF. The conventional UKF and the proposed adaptive UKF were compared with demonstrations of the attitude and attitude rate estimation of the satellite. Specifically, the Q (process noise covariance)-adaptation method is proposed. In the case of process noise increment, which may be caused by the changes in the environment or satellite dynamics, the performance of the Q-adaptive UKF was investigated.


Robust Estimation of UAV Dynamics in the Presence of Measurement Faults
Hacızade, Cengiz; Söken, Halil Ersin (American Society of Civil Engineers (ASCE), 2012-01-01)
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...
Adaptive Fading UKF with Q-Adaptation: Application to Picosatellite Attitude Estimation
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...
Adaptive Tuning of the Unscented Kalman Filter for Satellite Attitude Estimation
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...
Processing forced vibration test records of structural systems using the analytic signal
Çelik, Ozan Cem (SAGE Publications, 2020-09-01)
This article presents the use of the analytic signal procedure for processing the large volume of structural vibration data recorded in forced vibration tests. The analytic signal facilitates the computationally laborious task of extracting the steady-state amplitude for each response measure of interest from the recorded accelerations throughout the building at each operated frequency of the forced vibration source. The implementation of the signal processing procedure introduced here is illustrated in der...
Estimation of pico-satellite attitude dynamics and external torques via Unscented Kalman Filter
Söken, Halil Ersin (FapUNIFESP (SciELO), 2014-01-01)
In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The sa...
Citation Formats
C. Hacızade, H. E. Söken, and D. Cilden-Guler, “Nontraditional Attitude Filtering with Simultaneous Process and Measurement Covariance Adaptation,” JOURNAL OF AEROSPACE ENGINEERING, pp. 0–0, 2019, Accessed: 00, 2020. [Online]. Available: