Abstract
Several processing methods have been proposed for estimating the real pattern of the temporal location and spatial map of the lightning strikes. However, due to the complexity of lightning signals, providing accurate lightning maps estimation remains a challenging task. This paper presents a cross-correlation wavelet-domain-based particle swarm optimization (CCWD-PSO) technique for an accurate and robust representation of lightning mapping. The CCWD method provides an initial estimate of the lightning map, while the PSO attempts to optimize the trajectory of the lightning map by finding the optimal sliding window of the cross-correlation. The technique was further enhanced through the introduction of a novel lightning event extraction method that enables faster processing of the lightning mapping. The CCWD-PSO method was validated and verified using three narrow bipolar events (NBEs) flashes. The observed results demonstrate that this technique offers high accuracy in representing the real lightning mapping with low estimation errors.
Highlights
Accurate lightning mapping is a key step to real-time detection of lightning strikes
We proposed a cross-correlation wavelet-domain-based particle swarm optimization (CCWD-PSO) technique to improve the performance of lightning mapping
In order to observe its influence on the performance of the PSO-based searching algorithm, this study selected a maximum iteration number of 500 since the performance was not improved beyond this number
Summary
Accurate lightning mapping is a key step to real-time detection of lightning strikes. The ITF has been recognized as superior, compared to the other techniques, due to its capability of scanning more lightning events and performing continuous and quasi-continuous emission mapping from lightning pulses for enhanced 2D visualization [2]. Several ITF-based techniques have been proposed to estimate the lightning maps [3,4,5,6,7]. Others used the time difference of arrival (TDOA) and cross-correlation in both time and frequency domains [3,5,8]. Despite the major progress made in this field, there is still a need for further enhancement, especially in developing more robust techniques that are able to locate the lightning emissions and optimize the process of lightning mapping
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