Star point centroid positioning method for error suppression

Abstract

The invention relates to a star point positioning method, and in particular relates to an error-suppressed star point centroid positioning method. System errors and random errors of centroid method star point positioning are effectively suppressed. According to the method, the advantages of two types of centroid positioning methods including a centroid method and a curved surface fitting method are combined, the gray scale of the star point window image is processed through cubic spline fitting, the smoothness of the star point window image is improved, and the influence of random noise is restrained; algorithm defocusing is adopted, and under the condition that the signal-to-noise ratio of the system is not reduced, an interpolation algorithm is utilized to expand a light spot dispersionarea, and the image space sampling frequency is increased to suppress the influence of system errors. The method effectively suppresses the positioning error, combines the advantages of two types of centroid positioning methods, namely the centroid method and the curved surface fitting method, and has good noise immunity and high positioning precision.

Description

technical field [0001] The invention relates to a star point positioning method, in particular to an error-suppressed star point centroid positioning method. Background technique [0002] Star point detection is an important part of optical system index measurement. The positioning accuracy of the centroid of the star point image directly affects the debugging and detection of the optical system index. In the star sensor, the location of the centroid of the star image is particularly important, and its accuracy determines the accuracy of the attitude measurement of the star sensor. The centroid positioning of star point image has extensive and important application value in the detection and use of optical instruments. [0003] Commonly used star point image centroid positioning algorithms can be divided into two categories: one is Gaussian surface fitting method, parabolic surface fitting method and other three-dimensional surface fitting algorithms. The fitting calculat...

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Problems solved by technology

[0004] Aiming at the problem that the surface fitting algorithm is relatively complicated in the existing star point centroid positioning calculation, and the centroid method is easily disturbed by systematic errors and random errors, the present invention proposes an error-suppressed star point centroid positioning method, which combines the centroid method and curved surface The advantages of the fitting algorithm, starting from the principle of suppressing errors, do not rely on a specific star point imaging model to perform cubic spline fitting to suppress random errors, use cubic spline interpolation to realize algorithm defocus suppression system errors, and suppression of overall positioning errors to improve positioning accuracy

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