Time Invariant Sensor Tasking for Catalog Maintenance of LEO Space objects using Stochastic Geometry
Abstract
Catalog maintenance of space objects by limited number of ground-based sensors presents a formidable challenging task to the space community. This article presents a methodology for time-invariant tracking and surveillance of space objects in low Earth orbit (LEO) by optimally directing ground sensors. Our methodology aims to maximize the expected number of space objects from a set of ground stations by utilizing concepts from stochastic geometry, particularly the Poisson point process. We have provided a systematic framework to understand visibility patterns and enhance the efficiency of tracking multiple objects simultaneously. Our approach contributes to more informed decision-making in space operations, ultimately supporting efforts to maintain safety and sustainability in LEO.
Cite
@article{arxiv.2507.00076,
title = {Time Invariant Sensor Tasking for Catalog Maintenance of LEO Space objects using Stochastic Geometry},
author = {Partha Chowdhury and Harsha M and Chinni Prabhunath Georg and Arun Balaji Buduru and Sanat K Biswas},
journal= {arXiv preprint arXiv:2507.00076},
year = {2025}
}
Comments
This work has been accepted and presented at the 35th AAS/AIAA Space Flight Mechanics Meeting, 2025, Kaua'i, Hawai