标题： 用于使用随机几何的LEO空间物体目录维护的时不变传感器任务安排 显示英文标题

标题： Time Invariant Sensor Tasking for Catalog Maintenance of LEO Space objects using Stochastic Geometry

摘要： 通过有限数量的地面传感器维护空间物体目录，对航天界来说是一个艰巨的挑战任务。 本文提出了一种方法，用于通过最优引导地面传感器，对低地球轨道（LEO）中的空间物体进行时不变的跟踪和监视。 我们的方法旨在通过利用随机几何的概念，特别是泊松点过程，来最大化从一组地面站中获取的空间物体的预期数量。 我们提供了一个系统框架，以理解可见性模式并提高同时跟踪多个物体的效率。 我们的方法有助于在航天操作中做出更明智的决策，最终支持维持LEO安全和可持续性的努力。 显示英文摘要

摘要： 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.