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Proceedings Paper

Development of a computationally efficient algorithm for attitude estimation of a remote sensing satellite
Author(s): Amir Labibian; Amir Hossein Bahrami; Javad Haghshenas
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Paper Abstract

This paper presents a computationally efficient algorithm for attitude estimation of remote a sensing satellite. In this study, gyro, magnetometer, sun sensor and star tracker are used in Extended Kalman Filter (EKF) structure for the purpose of Attitude Determination (AD). However, utilizing all of the measurement data simultaneously in EKF structure increases computational burden. Specifically, assuming n observation vectors, an inverse of a 3n×3n matrix is required for gain calculation. In order to solve this problem, an efficient version of EKF, namely Murrell’s version, is employed. This method utilizes measurements separately at each sampling time for gain computation. Therefore, an inverse of a 3n×3n matrix is replaced by an inverse of a 3×3 matrix for each measurement vector. Moreover, gyro drifts during the time can reduce the pointing accuracy. Therefore, a calibration algorithm is utilized for estimation of the main gyro parameters.

Paper Details

Date Published: 29 September 2017
PDF: 21 pages
Proc. SPIE 10423, Sensors, Systems, and Next-Generation Satellites XXI, 1042326 (29 September 2017); doi: 10.1117/12.2280005
Show Author Affiliations
Amir Labibian, Satellite Research Institute (Iran, Islamic Republic of)
Amir Hossein Bahrami, Amirkabir Univ. of Technology (Iran, Islamic Republic of)
Javad Haghshenas, Satellite Research Institute (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 10423:
Sensors, Systems, and Next-Generation Satellites XXI
Steven P. Neeck; Jean-Loup Bézy; Toshiyoshi Kimura, Editor(s)

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