| 摘要: |
| 在航天遥测信息传输领域，深度学习技术的应用日益受到关注。综述了深度学习技术在解决航天遥测信息传输中面临的数据量大、通信实时性高、易受干扰和路径损失大等问题中的应用。通过分析深度学习在优化遥测数据传输体量、提升传输效率、保障传输安全和减少传输误差等方面的进展，揭示了深度学习技术在提高航天遥测信息传输性能中的潜力。同时，还探讨了深度学习技术在航天遥测信息传输中面临的挑战，并提出了相应的研究思路，旨在为构建智能化航天遥测信息传输系统提供理论支持和实践指导。 |
| 关键词: 航天测控 航天遥测信息传输 深度学习 机器学习 |
| DOI：10.20079/j.issn.1001-893x.240204003 |
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| 基金项目: |
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| Application of Deep Learning in Aerospace Telemetry Information Transmission:an Overview |
| SHI Yufeng,CHENG Yayong,TIAN Zhijun,SUN Dayuan,WANG Yizhe |
| (The 54th Research Institute of China Electronics Technology Group Corporation,Shijiazhuang 050081,China) |
| Abstract: |
| In the field of aerospace telemetry communication，the application of deep learning technology is increasingly gaining attention.The authors review the application of deep learning technology in addressing the challenges faced in space telemetry information transmission,such as large data volume,high communication real-time requirements,susceptibility to interference,and significant path loss.By analyzing the progress of deep learning in optimizing telemetry data transmission volume,improving transmission efficiency,ensuring transmission security,and reducing transmission errors,the authors reveal the potential of deep learning technology in enhancing the performance of space telemetry information transmission.Additionally,the challenges faced by deep learning technology in space telemetry information transmission are discussed and corresponding research ideas are proposed,aiming to provide theoretical support and practical guidance for the construction of intelligent space telemetry information transmission systems. |
| Key words: aerospace TT&C;aerospace telemetry information transmission deep learning machine learning |
