基于奇异值分解的星形传感器星形识别算法分析与改进

Mona Zahednamazi, Alireza Toloui
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引用次数: 0

摘要

本文对基于奇异值分解的星形识别算法进行了分析和改进。为了改进识别结果,对算法进行了修改。此外,本文还分析和模拟了视场尺寸和所用恒星数量对识别结果的影响,以及数据库中重复集的比率。此外,还考虑了基于奇异值和向量的两步识别过程。结果表明,改进算法在提高识别率和降低数据库中的重复集率方面具有优势。改进算法在 𝟏𝟎 ° × 𝟏𝟎 ° 和 𝟏𝟐 ° × 𝟏𝟐 ° 视场维度下的识别率始终高于 %97。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and improvement of star identification algorithm based on singular value decomposition for star sensor
This paper presents analysis and improvements on a star identification algorithm based on singular value decomposition . To improve the identification results, modifications have been made to the algorithm. Moreover, analysis and simulation are presented to investigate the effect of field of view dimensions and the number of stars used on the identification results, and the rate of duplicate sets in the database. In addition, identification has been considered a two-step process based on singular values and vectors. The results show the superiority of the improved algorithm in increasing the identification rate and reducing the rate of duplicate sets in the database. The identification rate of the improved algorithm in 𝟏𝟎 ° × 𝟏𝟎 ° and 𝟏𝟐 ° × 𝟏𝟐 ° fields of view dimension is always more the %97.
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