An Improved Method for Analyzing Broadband VHF Interferometer Lightning Observations

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Abstract
Based on the very high-frequency (VHF) pulse signal detected by interferometer (INTF) antennas as the reference unit, a lightning location method based on pulse matching and peak extraction is proposed in this paper. The first key step of this method is to optimize the raw VHF data of the INTF by using the ensemble empirical mode decomposition (EEMD) method to control the quality of the original signal by bandpass filtering to preserve only the relatively high-frequency components of 40-80 MHz. Then, through a combination of main and auxiliary windows, the matching of waveforms from different antennas is realized by means of generalized cross-correlation. In a microscale window (11 ns), the pulse signals are further accurately matched, and the arrival time difference is calculated under threshold and similarity constraints. Finally, the two-dimensional coordinates of the matched pulsed radiation sources are obtained using the nonlinear least squares method. Compared with the results of the traditional ’centroid’ approach, the number of radiation sources obtained with the proposed method is greatly increased. For lightning cases with different discharge intensities, the number of located radiation sources can be increased by a factor of 10-20, and for specific short-duration and rapidly changing discharge processes (such as dart leaders and K events), the number of located radiation sources can be increased by a factor of nearly 100. For INTF operation at 20-88 MHz with a sampling rate of 180 MHz, the analytical resolution of the lightning discharge process can be improved to 10 ns. When the radiation sources are fully located, the widths of the lightning channels can be successfully reconstructed from the density of no-size points representing the located radiation sources in space.
Funding Information
  • National Science Foundation (AGS 1720600, AGS 2214044)
  • National Natural Science Foundation of China (42175090)
  • China Postdoctoral Science Foundation (2020M670974)
  • Gansu Science and Technology Program (18JR2RA005)

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