Conducting surveillance of the geocenric orbits is a key task towards achieving space situational awareness (SSA). Our work focuses on the optical detection of man-made objects (e.g., satellites, space debris) in Geostationary orbit (GEO), which is home to major space assets such as telecommunications and Earth observing satellites. GEO object detection is challenging due to the distance of the targets, which appear as small dim point-like objects among a background of streak-like objects. In this paper, we propose a novel multi-target detection technique based on topological sweep, to find GEO objects from a short sequence of optical images. Our topological sweep technique exploits the geometric duality that underpins the approximately linear trajectory of target objects across the sequence, to extract the targets from significant clutter and noise. Unlike standard multi-target methods, our algorithm deterministically solves a combinatorial problem to ensure high-recall rates without requiring accurate initializations. The usage of geometric duality also yields an algorithm that is computationally efficient and suitable for online processing.

中文翻译：

---

对地静止空间物体多目标检测的拓扑扫描


对地心轨道进行监视是实现空间态势感知（SSA）的一项关键任务。我们的工作重点是对地球静止轨道（GEO）中的人造物体（例如卫星、空间碎片）进行光学探测，该轨道是电信和地球观测卫星等主要空间资产的所在地。由于目标距离较远，GEO 目标检测具有挑战性，目标在条纹状物体的背景中表现为小的暗淡点状物体。在本文中，我们提出了一种基于拓扑扫描的新型多目标检测技术，从短的光学图像序列中查找 GEO 物体。我们的拓扑扫描技术利用几何对偶性，支持目标对象在序列中的近似线性轨迹，从显着的杂波和噪声中提取目标。与标准多目标方法不同，我们的算法确定性地解决组合问题，以确保高召回率，而不需要精确的初始化。几何对偶性的使用还产生了一种计算效率高且适合在线处理的算法。