Abstract
The most accurate star centroiding method for star sensors is the Gaussian fitting (GF) algorithm, because the intensity distribution of a star spot conforms to the Gaussian function, but the computational complexity of GF is too high for real-time applications. In this paper, we develop the fast Gaussian fitting method (FGF), which approximates the solution of the GF in a closed-form, thus significantly speeding up the GF algorithm. Based on the fast Gaussian fitting method, a novel star centroiding algorithm is proposed, which sequentially performs the FGF twice to calculate the star centroid: the first FGF step roughly calculates the Gaussian parameters of a star spot and the noise intensity of each pixel; subsequently the second FGF accurately calculates the star centroid utilizing the noise intensity provided in the first step. In this way, the proposed algorithm achieves both high accuracy and high efficiency. Both simulated star images and star sensor images are used to verify the performance of the algorithm. Experimental results show that the accuracy of the proposed algorithm is almost the same as the GF algorithm, higher than most existing centroiding algorithms, meanwhile, the proposed algorithm is about 15 times faster than the GF algorithm, making it suitable for real-time applications.
Highlights
Star sensors are indispensable components of spacecraft attitude measurement systems.They capture images of stars with an imaging chip, and determine the three-axis attitude according to the location of stars in the field of view (FOV) [1]
The intensity of a de-focused star spot conforms to the “Airy disk”, which can be approximated by the Gaussian function [5]
Where xi and yi represent the i-th pixel in the image; xc and yc represent the centroid of the star spot in pixels; σx = σy = σr represents the standard deviation of the generated function of the star spot, and is defined as the Gaussian radius here; A represents the brightness level here; Ni represents the noise intensity of pixel i
Summary
Star sensors are indispensable components of spacecraft attitude measurement systems. They capture images of stars with an imaging chip, and determine the three-axis attitude according to the location of stars in the field of view (FOV) [1]. With the rapid development of space exploration [2,3,4], higher attitude accuracy is being more and more required, making it imperative to improve the accuracy of star sensors. Many factors can affect the accuracy of a star sensor, including the size of FOV, sensitivity of the imaging chip, distortion of the lens, accuracy of star centroiding, etc. A typical method to get an accurate star centroid is to make the star sensor slightly defocused, making the size of a star spot not smaller than 3 × 3 pixels. The task of a star centroiding algorithm is to estimate the centroid of the star spot
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