Adaptive filtering for lightning electric field (LEF) signals in fractional Fourier domain

This paper presents the application of an adaptive filtering algorithm, including the parameter estimation, in fractional Fourier transform domain (FRFd) for lightning electric field (LEF) signals. The adaptive algorithm in FRFd is based in the good energy concentration property of the fractional Fourier transform (FRFT). The proposed adaptive filtering algorithm integrates the advantages that LLMS and NLMS algorithms possess, introducing a leakage factor to reduce the memory effect when tracking a non-stationary signal. Moreover, the step-size is normalized to reduce the effect of the input signal power on the algorithm performance. The SNR behavior of the output filtered signal is analyzed for different LEF signals, showing that the proposed algorithm have better performance in low SNR environment.