中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2025, Vol. 51 ›› Issue (1): 105-114.doi: 10.3969/j.issn.1674 1579.2025.01.011

• 论文与报告 • 上一篇    下一篇

基于多特征融合的空间多目标在轨检测方法

  

  1. 北京控制工程研究所
  • 出版日期:2025-02-26 发布日期:2025-03-07
  • 基金资助:
    国家自然科学基金资助项目 (52275083)和空间智能控制技术全国重点实验室资助项目(2023JCJQLB00602)

A Method of Space Multi-Targets on-Orbit Detection Based on Multi-Feature Fusion

  • Online:2025-02-26 Published:2025-03-07

摘要: 在轨光学观测不受云层、大气、白昼等因素干扰,在时空范围及使用成本上均优于传统地基测量.立足于空间非合作目标在轨检测跟踪需求,提出一种空间多目标在轨检测方法,该方法首先利用Delaunay三角匹配实现恒星背景差分,并通过融合目标光度学、形态学与运动学特征进行轨迹关联,最终进行轨迹识别实现空间目标鲁棒检测.在密集星场多目标观测仿真数据集以及外场目标观测实验中多目标跟踪准确率均大于95%,能够在不依赖星表进行姿态解算、相机标定参数和目标先验信息的情况下有效输出多目标轨迹,相较于传统算法减小了运算量,提高了空间目标在轨检测能力,为空间多目标检测跟踪研究提拱参考.

关键词: 空间非合作目标, 在轨检测跟踪, Delaunay三角匹配, 多特征融合

Abstract: On orbit optical observations are not affected by factors such as clouds, atmosphere and daylight, and are superior to traditional ground based measurements in terms of temporal and spatial range and cost of use. Based on the needs of on orbit detection and tracking of non cooperative space targets, the paper proposes a method for on orbit detection of space multi targets. This method first uses Delaunay triangulation matching to achieve stellar background differentiation, and then integrates the target photometric, morphological and kinematic features to perform trajectory association, and finally performs trajectory recognition to achieve robust detection of space targets. In the simulation data set of dense star field multi target observations and field target observation experiments, the multiple object tracking accuracy is greater than 95%, and it can effectively output multi target trajectories without relying on star catalogs for attitude solution, camera calibration parameters and target prior information. Compared with traditional algorithms, it reduces the amount of calculation and improves the onorbit detection capability of space targets.

Key words: uncertainty, time delay, non-cooperative targets in space, on-orbit detection and tracking, delaunay triangle matching, multi-feature fusion

中图分类号: 

  • V44