一种基于星图灰度分布特征的星敏感器质量分类方法

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摘要针对传统依据人工判读星敏感器成像图像方法的低效性，以及产品质量信息人工判读可靠性差、可用性低、识别效率低等问题，本文以星敏感器的构造原理为基础，对星图进行阈值降噪处理。依据多张去噪后星图的灰度分布特征，构建产品质量特征模型，并以此模型结合光学像差成像原理建立产品质量分类模型。该模型可满足产品总装质量的智能分类需求，使得产品质量信息的判读更具可靠性、可操作性以及可用性，有效降低生产成本，提高生产效率。

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关键词 ：星敏感器, 阈值降噪, 灰度分布特征, 光学像差成像原理, 质量分类, 星图

Abstract：The traditional manual interpretation methods for star sensor imaging images are ineffective and limit manual interpretation of product quality information, which can lead to low reliability, usability, and recognition efficiency. Based on the structural principle of star sensors, this paper employed threshold denoising for star images. It constructed a product quality feature model using the grayscale distribution characteristics of multiple denoised star maps. Combined with the principle of optical aberration imaging, this model established a product quality classification model to satisfy the intelligent classification requirements for product assembly quality, interpreting product quality information as more reliable, operable, and usable, effectively reducing production costs and time.

Key words： star sensor threshold denoising grayscale distribution characteristics optical aberration imaging principle quality classification star map

收稿日期: 2024-07-22 出版日期: 2025-05-23

ZTFLH:

TP 391.4

基金资助:上海市城市数字化转型专项资金(202301061)；上海市经济和信息化委员会专项资金(2221103)

通讯作者: 叶宋杭

作者简介: 作者简介：练鹏（1994—），男，硕士，助理工程师。

引用本文:

练鹏, 杨积东, 叶宋杭, 占晓敏. 一种基于星图灰度分布特征的星敏感器质量分类方法[J]. 空天防御, 2025, 8(2): 118-124.
LIAN Peng, YANG Jidong, YE Songhang, ZHAN Xiaomin. A Quality Classification Method for Star Sensor Based on Gray-Scale Distribution Characteristics of Star Maps. Air & Space Defense, 2025, 8(2): 118-124.

链接本文:

https://www.qk.sjtu.edu.cn/ktfy/CN/ 或 https://www.qk.sjtu.edu.cn/ktfy/CN/Y2025/V8/I2/118