空天防御2025，Vol.8Issue(2)：118-124,7.
一种基于星图灰度分布特征的星敏感器质量分类方法
A Quality Classification Method for Star Sensor Based on Gray-Scale Distribution Characteristics of Star Maps
摘要
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.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Key words
star sensor/threshold denoising/grayscale distribution characteristics/optical aberration imaging principle/quality classification/star map分类
信息技术与安全科学引用本文复制引用
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):118-124,7.基金项目
上海市城市数字化转型专项资金(202301061) （202301061）
上海市经济和信息化委员会专项资金(2221103) （2221103）
