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Automatic recognition of tweek atmospherics and plasma diagnostics in the lower ionosphere with the machine learning method
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作者 Mao Zhang GaoPeng Lu +5 位作者 HaiLiang Huang ZhengWei Cheng YaZhou Chen Steven A.Cummer JiaYi Zheng JiuHou Lei 《Earth and Planetary Physics》 EI CSCD 2023年第3期407-413,共7页
Tweek atmospherics are extremely low frequency and very low frequency pulse signals with frequency dispersion characteristics that originate from lightning discharges and that propagate in the Earth–ionosphere wavegu... Tweek atmospherics are extremely low frequency and very low frequency pulse signals with frequency dispersion characteristics that originate from lightning discharges and that propagate in the Earth–ionosphere waveguide over long distances.In this study,we developed an automatic method to recognize tweek atmospherics and diagnose the lower ionosphere based on the machine learning method.The differences(automatic−manual)in each ionosphere parameter between the automatic method and the manual method were−0.07±2.73 km,0.03±0.92 cm^(−3),and 91±1,068 km for the ionospheric reflection height(h),equivalent electron densities at reflection heights(Ne),and propagation distance(d),respectively.Moreover,the automatic method is capable of recognizing higher harmonic tweek sferics.The evaluation results of the model suggest that the automatic method is a powerful tool for investigating the long-term variations in the lower ionosphere. 展开更多
关键词 machine learning method tweek atmospherics reflection height D-region ionosphere
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