Abstract—The Canadian National (CN) Tower is a transmission tower and it is not unexpected that recorded lightning current signals be corrupted by noise. The existence of noise may affect the calculation of current waveform parameters (current peak, 10-90% risetime to current peak, maximum steepness, and pulse width at half value of current peak). To determine accurate statistics of current waveform parameters, the interfering noise must be removed. In this paper, a Short Term Fourier Transform (STFT)-based Spectral Subtraction method is developed to de-noise the lightning current derivative signal measured at the CN Tower. In order to evaluate the proposed de-noising method, a simulated current derivative waveform is used after being artificially distorted by a noise signal measured at the CN Tower in the absence of lightning. The de-noised waveform proved to be very close to the original simulated waveform. The STFT-based Spectral Subtraction method is then applied successfully to de-noise the lightning current derivative signal recorded at the CN Tower. A signal peak-to-noise peak ratio (SPNPR) of the lightning current signal is defined and calculated before and after the de-noising procedure.

Index Terms—CN Tower, Current Derivative Signal, Spectral Subtraction Method

M. J. Islam is a doctoral student in Electrical and Computer Engineering Department of University of Windsor, Windsor, ON. Canada.
A. M. Hussein is a Professor of Electrical and Computer Engineering Department of Ryerson University, Toronto, ON, Canada.

Cite: M. J. Islam and A. M. Hussein, "Frequency Domain Approach to De-Noise the CN Tower Lightning Current Derivative Signal and Its Parameters Calculations," International Journal of Computer and Electrical Engineering vol. 1, no. 3, pp. 328-333, 2009.