This paper aims to examine different star identification algorithms in star sensors and compare the previous algorithms with the newly proposed algorithms. The star identification algorithms in this paper include three geometric methods, which require a minimum of five stars in the sensor field of view. These algorithms are compared with the angle, combined triangle, and pyramid algorithms in terms of speed, accuracy, storage capacity, and resistance to false stars using MATLAB software. Except for the angle algorithm, all the other star identification algorithms have high precision and resistance to false stars. In addition, they have a lower speed than those of the algorithms that use fewer stars to form the pattern. Considering the number of stars required for the algorithm, the newly proposed star identification algorithms are suitable for the second generation of star sensors, which have a larger field of view. The simulations are related to the stars brighter than magnitude 4, as well as a star sensor with a square-shaped field of view with a dimension of 13.8 ∘ × 13.8 ∘ $13.8^{\circ }\times 13.8^{\circ }$ , similar to the ASTRO 15 sensor manufactured by Jena-Optronik GmbH company.

中文翻译：

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恒星识别算法对比分析

本文旨在研究星敏感器中不同的星识别算法，并将以前的算法与新提出的算法进行比较。本文中的恒星识别算法包括三种几何方法，它们要求传感器视场中至少有五颗星。使用MATLAB软件将这些算法与角度、组合三角形和金字塔算法在速度、精度、存储容量和抗伪星能力等方面进行了比较。除角度算法外，其他所有恒星识别算法都具有较高的精度和抗伪星能力。此外，它们的速度低于使用较少星星来形成图案的算法。考虑到算法所需的星数，新提出的恒星识别算法适用于视场更大的第二代星敏感器。模拟与亮度大于 4 等的恒星以及具有方形视场的星敏感器有关，其尺寸为 13.8 ∘ × 13.8 ∘ $13.8^{\circ }\times 13.8^{\circ }$ ，类似于 Jena-Optronik GmbH 公司生产的 ASTRO 15 传感器。