Research on Motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting

doi:10.1007/s12204-018-1943-8

Abstract

Abstract: The energy distribution model of motion blurred star point is analyzed. The distribution of the star point approximates to a two-dimensional (2D) Gaussian distribution under degeneration. Two multi-parameter nonlinear Gaussian fitting methods (GFMs) are proposed, and the relationship between fitting parameters and motion blur parameters is analyzed. Estimation of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion blur. The simulation results show the effectiveness and accuracy.

Key words: star sensors| centroid calculation| Gaussian fitting method (GFM)| motion blur

摘要： The energy distribution model of motion blurred star point is analyzed. The distribution of the star point approximates to a two-dimensional (2D) Gaussian distribution under degeneration. Two multi-parameter nonlinear Gaussian fitting methods (GFMs) are proposed, and the relationship between fitting parameters and motion blur parameters is analyzed. Estimation of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion blur. The simulation results show the effectiveness and accuracy.

关键词: star sensors| centroid calculation| Gaussian fitting method (GFM)| motion blur

CLC Number:

TP 391

WANG Chaoran (王超然), BAO Qilian (鲍其莲), ZHENG Xunjiang (郑循江), SUN Shuodong (孙朔冬). Research on Motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(4): 562-.

References 11

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