居住空间物体 (RSO) 检测方法的比较分析
Vithurshan Suthakar1, Aiden Alexander Sanvido2, Randa Qashoa1
1Department of Earth and Space Science, York University, Toronto, ON M3J 1P3, Canada.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
检测居住空间物体 (RSO) 对太空安全至关重要. 本研究引入了新的注释图像数据集,并评估了用于改进RSO检测和空间局势意识的差分技术.
科学领域:
- 太空监视和跟踪 太空监视和跟踪
- 天体动力学是指天体动力学.
- 光学遥感器 远程传感器
背景情况:
- 越来越多的卫星发射导致地球轨道上居住空间物体 (RSO) 的激增.
- 准确检测RSO对于避免碰撞和保持空间局势意识 (SSA) 来说至关重要.
- 公共数据集的有限可用性阻碍了开发有效的RSO检测算法.
研究的目的:
- 为了呈现一个新的,内部策划的数据集,注释住宿空间物体 (RSO) 图像.
- 使用此数据集,评估各种差分技术用于RSO检测的有效性.
- 为提高空间局势意识 (SSA) 的算法进步做出贡献.
主要方法:
- 从平流层气球平台获取低分辨率,宽视野图像.
- 对图像进行注释,以创建用于RSO检测的数据集.
- 实施和评估四个区分算法:相邻区分,中位区分,近距离过和跟踪以及线条检测.
主要成果:
- 评估的算法在RSO检测中表现出不同程度的成功.
- 精度得分从73%到100%不等,线条检测达到最高的精度.
- F1得分从68%到82%不等,表明测试方法在识别RSO方面的有效性.
结论:
- 开发的注释式RSO图像数据集支持检测算法的评估.
- 差异化技术,特别是连续检测,显示了提高RSO检测能力的重大前景.
- 这些方法的进一步开发和应用可以改善空间局势意识 (SSA) 和空间交通管理.
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