卫星频谱信号智能挖掘技术

doi:10.11959/j.issn.2096-8930.2022029

天地一体化信息网络 ›› 2022, Vol. 3 ›› Issue (3): 30-36.doi: 10.11959/j.issn.2096-8930.2022029

所属专题：专题：智能+卫星互联网

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卫星频谱信号智能挖掘技术

吕秋霖¹^,³, 丁晓进¹^,³, 张更新²^,³

¹ 南京邮电大学物联网学院，江苏南京 210003
² 南京邮电大学通信与信息工程学院，江苏南京 210003
³ 南京邮电大学卫星通信研究所，江苏南京 210003

修回日期:2022-07-06 出版日期:2022-09-20 发布日期:2022-09-01
作者简介:吕秋霖（1996-），男，南京邮电大学物联网学院硕士生，主要研究方向为卫星频谱智能认知
丁晓进（1981-），男，南京邮电大学物联网学院副教授，主要研究方向为空间信息网络、卫星物联网、频谱智能认知等
张更新（1967-），男，南京邮电大学通信与信息工程学院教授，主要研究方向为空间信息网络、卫星通信等
基金资助:
国家自然科学基金资助项目(62171234);国家自然科学基金资助项目(U21A20450);国家自然科学基金资助项目(61971440);江苏省前沿引领技术基础研究专项(BK20192002)

Intelligent Excavation Technologies for Satellite Spectrum Signals

Qiulin LYU¹^,³, Xiaojin DING¹^,³, Gengxin ZHANG²^,³

¹ College of Internet of Things, Nanjing University of Post and Telecommunications, Nanjing 210003, China
² College of Telecommunications ＆Information Engineering, Nanjing University of Post and Telecommunications, Nanjing 210003, China
³ Satellite Communication Research Institute, Nanjing University of Post and Telecommunications, Nanjing 210003, China

Revised:2022-07-06 Online:2022-09-20 Published:2022-09-01
Supported by:
The National Natural Science Foundation of China(62171234);The National Natural Science Foundation of China(U21A20450);The National Natural Science Foundation of China(61971440);Jiangsu Province Basic Research Project(BK20192002)

摘要/Abstract

摘要：

随着空间信息网络的建设，可用频谱资源日益紧缺，面临的电磁环境越来越复杂，实现对全球电磁频谱态势的安全掌控所面临的挑战更加突出。针对以上问题，研究电磁频谱占用状态感知方法，通过构建时间卷积神经网络来感知频谱占用状态；探索频谱参数提取方法，结合底噪拟合和聚类分析，实现对中心频率、带宽、峰值功率等参数的提取；为挖掘异常频谱数据，研究利用神经网络自动检测起伏底噪、频谱草和大带宽等异常频谱；考虑星地间的大传播时延，进一步通过构建神经网络来实现对频谱占用状态的预测；将卫星频谱信号的感知、异常、参数和预测结果进行可视化呈现。初步评估结果表明，所设计的一套频谱感知、异常检测、参数认知和态势预测等卫星频谱智能挖掘技术，在提升频谱态势安全掌控能力的同时，还能有效提升频谱资源利用率。

关键词: 频谱感知, 参数认知, 异常检测, 频谱态势

Abstract:

With the construction of spatial information network, the available spectrum resources are increasingly scarce, and the electromagnetic environment is becoming more and more complex, resulting a more prominent challenge of realizing the safe control of the global electromagnetic.Therefore, the sensing method of electromagnetic spectrum occupation state was studied, a time convolution neural network to sense the spectrum occupation state was constructed.To mine abnormal spectrum data, neural network was used to automatically detect abnormal spectrum, such as fl uctuation noise fl oor, spectrum grass and large bandwidth.The spectrum parameter extraction method was explored.Considering the large propagation delay between the spectrum-sensing satellite and its gateway, a neural network was constructed to predicted the spectrum occupation state.The perception, anomaly, parameters and prediction results of satellite spectrum signal were visualized.The preliminary evaluation results showed that the designed satellite-spectrum intelligent mining technologies could not only improved the sensing ability of spectrum situation, but also eff ectively improved the utilization of spectrum resources.

Key words: spectrum sensing, parameters recognition, abnormal detection, spectrum situation

中图分类号:

吕秋霖, 丁晓进, 张更新. 卫星频谱信号智能挖掘技术[J]. 天地一体化信息网络, 2022, 3(3): 30-36.

Qiulin LYU, Xiaojin DING, Gengxin ZHANG. Intelligent Excavation Technologies for Satellite Spectrum Signals[J]. Space-Integrated-Ground Information Networks, 2022, 3(3): 30-36.

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卫星频谱信号智能挖掘技术

Intelligent Excavation Technologies for Satellite Spectrum Signals

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