Original article can be found at: http://www.sciencedirect.com/ Copyright ElsevierThe lightning current derivative data recorded at the CN Tower during the past 18 years contain different kinds of noise and needs to be denoised for accurately determining the lightning current waveform parameters. It is usually a challenging task to denoise transient signals having large bandwidth without altering their waveshapes or shrinking their amplitudes. This paper deals with denoising the CN Tower lightning current derivative signals using several adaptive techniques. A new adaptive denoising approach (Divide-and-Conquer) has been successfully used to denoise a vast variety of CN Tower lightning current derivative waveshapes. The supremacy of the new technique over the existing ones is outlined for a signal with a poor signal-to-noise ratio (SNR). While keeping the signal amplitude unchanged and preserving its waveshape, the new denoising technique improved its SNR from ???22.93 dB to 71.41 dB
Abstract-The CN Tower is a transmission hub and an instrumented tower for the measurement of the lightning return stroke current derivative. The recorded data are corrupted by different kinds of noise, and need to be denoised for accurate determination of the lightning return-stroke current waveform parameters. A new Divide-and-Conquer denoising approach that imitates the Basis Pursuit method and the Newton-Raphson technique has been developed. This paper describes the new process of denoising the recorded signals. First, the current derivative is preprocessed to eliminate the noise outside the lightning return-stroke active region and reduce the presence of the high frequencies inside the active region. Then, by marching on both the graphs of the current derivative and its integral, the noise due to reflections is localized and removed. By this process the SNR improved by 35 dB and the lightning current and current derivative parameters are calculated automatically with a high precision. Furthermore, using the calculated parameters the data is curve fitted to Heidler function, which results in a model for the measured lightning current derivative with an infinite SNR.
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