Neuromorphic Vision-Based Dataset for Space Situational Awareness Applications
收藏科学数据银行2025-10-09 更新2026-04-23 收录
下载链接：
https://www.scidb.cn/detail?dataSetId=eb88043fa0124cdcb0f2b44ee0ec274c
下载链接
链接失效反馈官方服务：
资源简介：
The space technology sector witnesses the increasing density of space debris and defunct satellites in Earth orbit. Space debris poses growing risks to future space missions and operations that intensified the need for advanced Space Situational Awareness (SSA) technologies. Neuromorphic vision sensors (NVS) offer a potential alternative to conventional optical and radar ground systems, providing microsecond temporal resolution, high dynamic range, and high altitude observations. In this work, we present a new labeled dataset for real-time detection and tracking of Resident Space Objects (RSOs). The data is acquired using two neuromorphic sensors DAVIS346 and DVXplorer640 integrated with a high-precision 0.8 m aperture Ritchey–Chrétien telescope. The dataset includes event-based recordings of 15 satellites and space debris, along with stars of varying brightness for performance benchmarking. The data is annotated to support supervised training of deep learning models. This dataset is a foundation for developing high-performance RSO detection AI algorithms, such as flash attention-based networks.
提供机构：
Afnan Ahmed Adil; Technology Innovation Institute; Khalifa University of Science and Technology
创建时间：
2025-09-20
