Constant-gain EKF algorithm for satellite attitude determination systems. Issue 8 (5th November 2018)

• Record Type: Journal Article
• Authors: Hua, Song; Huang, Huiyin; Yin, Fangfang; Wei, Chunling
• Is Part Of: Aircraft engineering and aerospace technology. Volume 90:Issue 8(2018)
• Page Start: 1259
• Page End: 1271
• Publication Date: 2018-11-05
• Subjects: Projection method -- Kalman filter -- Constant-gain -- Satellite attitude determination system -- Star tracker; Aerospace engineering -- Periodicals; Aeronautics -- Systems engineering -- Periodicals; Astronautics -- Systems engineering -- Periodicals; Airplanes -- Equipment and supplies -- Periodicals; Space vehicles -- Equipment and supplies -- Periodicals; Aerospace industries -- Periodicals; 629.1
• DOI: 10.1108/AEAT-03-2017-0088
• Languages: English
• ISSNs: 1748-8842

Abstract

Abstract : Purpose: This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors. Design/methodology/approach: First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm. Findings: The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers. Originality/value: In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm.