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Attitude Correlated Frames Based Calibration Method for Star Sensors.
Ma, Liheng; Xiao, Shenglong; Tang, Wenjun; Luo, Xiao; Zhang, Su.
Afiliação
  • Ma L; College of Ordnance Engineering, Naval University of Engineering, Wuhan 430033, China.
  • Xiao S; Guangzhou Bureau of the Department of Naval Equipment, Guangzhou 511464, China.
  • Tang W; Guangzhou Bureau of the Department of Naval Equipment, Guangzhou 511464, China.
  • Luo X; Guangzhou Bureau of the Department of Naval Equipment, Guangzhou 511464, China.
  • Zhang S; College of Ordnance Engineering, Naval University of Engineering, Wuhan 430033, China.
Sensors (Basel) ; 24(1)2023 Dec 22.
Article em En | MEDLINE | ID: mdl-38202931
ABSTRACT
Star sensors undergo laboratory calibration before they leave the factory. In addition, recalibration is necessary after they experience vibration, deformation, etc. Using the analysis of attitude-dependent and attitude-independent interstar angular invariance calibration methods (IAICMs) as a reference, an attitude-correlated frame-based calibration method (ACFCM) is proposed in this work, which combines the advantages of both methods. Using outdoor star observations, the ACFCM correlates star image frames obtained at different times via a strapdown gyro unit. As a result, the number of efficient star images for calibration increases rapidly and the distribution of star images becomes much more uniform, thus improving the calibration accuracy of the star sensor. A simulation and experimental tests were designed and carried out. Both the simulation and experimental results verify the feasibility of the proposed ACFCM method. Furthermore, by comparing our method with the IAICMs, the repeatability and reliability of the principal point obtained from the calibration with the ACFCM method proposed in this work were significantly improved.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article