# Topological Sweep for Multi-Target Detection of Geostationary Space Objects

arXiv: https://arxiv.org/abs/2003.09583 · HTML: https://mlsanity.com/paper/2003.09583/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2020.

## Built on by (most cited first, 3 of 3)

- [SSTD: Stripe-Like Space Target Detection Using Single-Point Weak Supervision](https://mlsanity.com/paper/2407.18097/) (2024)
- [Beyond Motion Cues and Structural Sparsity: Revisiting Small Moving Target Detection](https://mlsanity.com/paper/2509.07654/) (2025)
- [Space Object Detection using Multi-frame Temporal Trajectory Completion Method](https://mlsanity.com/paper/2510.19220/) (2025)

## Abstract (arXiv)

Conducting surveillance of the Earth's orbit 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 navigational satellites. GEO object detection is challenging due to the distance of the targets, which appear as small dim points among a clutter of bright stars. 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 input 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.