To ensure the secure operation of space assets, it is crucial to employ ground and/or space-based surveillance sensors to observe a diverse array of anthropogenic space objects (ASOs). This enables the monitoring of abnormal behavior and facilitates the timely identification of potential risks, thereby enabling the provision of continuous and effective Space Situational Awareness (SSA) services. One of the primary challenges in this endeavor lies in optimizing the tasking of surveillance sensors to maximize SSA capabilities. However, the complexity of the space environment, the vast number of ASOs, and the limitations imposed by available sensor resources present significant obstacles to effective sensor management. To tackle these challenges, various sensor tasking methods have been developed over the past few decades. In this paper, we comprehensively outline the fundamental characteristics of sensor tasking missions, and later examine the corresponding objective functions and algorithms employed for efficient optimization, respectively. Furthermore, we explore the practical application of sensor tasking methods in diverse organizations and provide insights into potential directions for future research, aiming to stimulate further advancements in this field.

中文翻译：

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空间态势感知中传感器任务分配方法综述


为了确保空间资产的安全运行，使用地面和/或天基监视传感器来观察各种人造空间物体（ASO）至关重要。这使得能够监控异常行为并有助于及时识别潜在风险，从而能够提供持续有效的空间态势感知（SSA）服务。这项工作的主要挑战之一在于优化监视传感器的任务分配，以最大限度地提高 SSA 功能。然而，太空环境的复杂性、大量的 ASO 以及可用传感器资源的限制给有效的传感器管理带来了重大障碍。为了应对这些挑战，过去几十年来开发了各种传感器任务分配方法。在本文中，我们全面概述了传感器任务分配任务的基本特征，然后分别研究了用于有效优化的相应目标函数和算法。此外，我们探索传感器任务分配方法在不同组织中的实际应用，并为未来研究的潜在方向提供见解，旨在促进该领域的进一步进步。