Robust adaptive unscented Kalman filter for attitude estimation of pico satellites

Date

2014-02-01

Author

Hacızade, Cengiz
Söken, Halil Ersin

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Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault-tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q-adaptation) or measurement noise covariance (R-adaptation) depending on the type of the fault. By the use of a newly proposed adaptation scheme for the conventional UKF algorithm, the fault is detected and isolated, and the essential adaptation procedure is followed in accordance with the fault type. The proposed algorithm is tested as a part of the attitude estimation algorithm of a pico satellite. Copyright (c) 2013 John Wiley & Sons, Ltd.

Subject Keywords

Control and Systems Engineering, Signal Processing, Electrical and Electronic Engineering

URI

https://hdl.handle.net/11511/69785

Journal

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING

DOI

https://doi.org/10.1002/acs.2393

Collections

Department of Aerospace Engineering, Article

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Citation Formats

C. Hacızade and H. E. Söken, “Robust adaptive unscented Kalman filter for attitude estimation of pico satellites,” INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, pp. 107–120, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69785.