With the rapid increase of space activities and the accumulation of space debris, the existing space situational awareness systems (SSAS) is facing increasingly severe challenges. This paper analyzes traditional approaches and describes their limitations in dealing with complex space environments. To address these challenges, we explore the application of artificial intelligence (AI) technology in SSAS and its future development scenarios. This paper gives a detailed overview of the basic principles and applications of traditional SSAS, and highlights its limitations. We focus on the application of AI to orbit determination and orbit prediction, highlighting its potential to enhance system flexibility and adaptability. In addition, we present possible directions for the future development of AI technology in SSAS. By combining traditional methods with AI technologies, we can expect more efficient and intelligent systems that are able to adapt to complex space environments. Through this comprehensive perspective, this paper aims to provide an in-depth understanding of SSAS and provide a valuable reference for future technological innovations and system upgrades.

中文翻译：

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空间态势感知系统：连接传统方法和人工智能


随着太空活动的迅速增加和太空碎片的积累，现有的空间态势感知系统（SSAS）面临着日益严峻的挑战。本文分析了传统方法，并描述了它们在处理复杂空间环境方面的局限性。为了应对这些挑战，我们探讨了人工智能 （AI） 技术在 SSAS 中的应用及其未来的发展场景。本文详细概述了传统 SSAS 的基本原理和应用，并强调了其局限性。我们专注于人工智能在定轨和轨道预测中的应用，强调其增强系统灵活性和适应性的潜力。此外，我们还为 SSAS 中人工智能技术的未来发展提出了可能的方向。通过将传统方法与 AI 技术相结合，我们可以期待能够适应复杂太空环境的更高效、更智能的系统。本文旨在通过这种全面的视角，提供对 SSAS 的深入理解，并为未来的技术创新和系统升级提供有价值的参考。