TY - JOUR
T1 - Review of sensor tasking methods in Space Situational Awareness
AU - Xue, Chenbao
AU - Cai, Han
AU - Gehly, Steve
AU - Jah, Moriba
AU - Zhang, Jingrui
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/5/1
Y1 - 2024/5/1
N2 - 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.
AB - 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.
KW - Catalog maintenance
KW - Heuristic algorithm
KW - Information gain
KW - Multi-objective optimization
KW - Reinforcement learning
KW - Sensor tasking
KW - Space Situational Awareness
KW - Space Surveillance Network
UR - http://www.scopus.com/inward/record.url?scp=85195851584&partnerID=8YFLogxK
U2 - 10.1016/j.paerosci.2024.101017
DO - 10.1016/j.paerosci.2024.101017
M3 - Review article
AN - SCOPUS:85195851584
SN - 0376-0421
VL - 147
JO - Progress in Aerospace Sciences
JF - Progress in Aerospace Sciences
M1 - 101017
ER -