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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2507.00076 |
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| _version_ | 1866911030245851136 |
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| author | Chowdhury, Partha M, Harsha Georg, Chinni Prabhunath Buduru, Arun Balaji Biswas, Sanat K |
| author_facet | Chowdhury, Partha M, Harsha Georg, Chinni Prabhunath Buduru, Arun Balaji Biswas, Sanat K |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_00076 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Time Invariant Sensor Tasking for Catalog Maintenance of LEO Space objects using Stochastic Geometry Chowdhury, Partha M, Harsha Georg, Chinni Prabhunath Buduru, Arun Balaji Biswas, Sanat K Instrumentation and Methods for Astrophysics Robotics Systems and Control Mathematical Physics 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. |
| title | Time Invariant Sensor Tasking for Catalog Maintenance of LEO Space objects using Stochastic Geometry |
| topic | Instrumentation and Methods for Astrophysics Robotics Systems and Control Mathematical Physics |
| url | https://arxiv.org/abs/2507.00076 |