Centroiding Method for Star Image Spots under Interference of Sun Straylight Noise in a Star Sensor

Centroiding Method for Star Image Spots under Interference of Sun Straylight Noise in a star sensor: To secure the centroiding accuracy of star image spots under the interference of sun straylight noise, we proposed a new centroiding method featuring the subtraction of background threshold and straylight slope noise in this paper. First, the gray noise of sun straylight was modeled as a slope within the window of a star image spot. For the new centroiding method, the error analysis equation of centroiding was deduced regarding the parameter estimation errors of the straylight slope model, especially the function relation concerning the window size. Then, the least-square parameter estimation formulas for the straylight slope model were given based on the window edge pixels. Finally, simulation tests were conducted through three centroiding methods, namely, the traditional gray weighted centroiding method(GWCM), the threshold subtracted GWCM, and the new method. The testing results show that the centroiding accuracy of the proposed method is two times and fifteen times higher than that of the two traditional methods. In conclusion, the method proposed in this paper is an effective centroiding method for star image spots under the interference of sun straylight noise and has a certain value in engineering applications.

This article establishes a new centroid localization method for removing threshold and stray light slant noise, ensuring the accuracy of star image point centroid localization under the interference of solar stray light. Modeling the grayscale noise of solar stray light as a slope is reasonable within the small window of the star map, and parameter estimation for simple slopes has high computational efficiency. An error analysis was conducted on the new method, and a centroid positioning error formula was derived with the estimation error of stray light slope and background threshold parameters as independent variables; The quantitative relationship between centroid positioning error and window edge length was revealed, and visual simulation and analysis were conducted, providing a theoretical basis for determining window size in engineering. This article provides a slope parameter estimation method based on window edge pixels and a least squares parameter estimation formula, thus forming a complete technical method. The proposed method improves the accuracy by 2 and 15 times compared to the traditional grayscale center of gravity method and thresholding centroid method, respectively. It is an effective method for locating the centroid of star image points under the interference of solar clutter and has high engineering application value.