RFI intelligent monitoring techniques for FAST

ZHANG Haiyan; HU Hongliang; WANG Yu; JIANG Huajing; GAN Hengqian; HU Hao; HUANG Shijie

doi:10.16511/j.cnki.qhdxxb.2022.26.030

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Journal of Tsinghua University(Science and Technology) ›› 2022, Vol. 62 ›› Issue (11) : 1780-1788. DOI: 10.16511/j.cnki.qhdxxb.2022.26.030

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RFI intelligent monitoring techniques for FAST

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Abstract

Radio frequency interference (RFI) intelligent monitoring techniques are being developed for the electromagnetic environment of the five-hundred-meter aperture spherical radio telescope (FAST), including interference source classification and identification and high-precision localization. According to the characteristics of FAST sites, the interference detection and identification uses multi-site cooperative spectrum sensing and signal identification based on deep neural networks. The interference source localization uses time difference of arrival (TDOA) for accurate localization with low signal-to-noise ratios. The time difference between signals arriving at different receivers is estimated using the generalized mutual correlation method. This intelligent monitoring research lays the groundwork for the FAST radio interference intelligent monitoring system as well as the FAST spectrum management and electromagnetic environmental protection work.

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FAST / radio frequency interference / interference identification and localization

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ZHANG Haiyan, HU Hongliang, WANG Yu, JIANG Huajing, GAN Hengqian, HU Hao, HUANG Shijie. RFI intelligent monitoring techniques for FAST[J]. Journal of Tsinghua University(Science and Technology). 2022, 62(11): 1780-1788 https://doi.org/10.16511/j.cnki.qhdxxb.2022.26.030

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