Detection for signal in ELF atmospheric noise interference

Extremely low frequency (ELF) atmospheric noise is non-Gaussian, consisting of the sum of a Gaussian background and narrow pulses caused by lighting strokes. Therefore, the conventional detection method for signal in Gaussian noise gets worse. In this paper, a new structure for signal detection in the ELF atmospheric noise is proposed. First, the ELF atmospheric noise is modeled as a symmetric α-stable (SαS) process. Then the performance of optimum linear detector, matched filter, and locally optimum detector are examined. The FFT-based algorithm is used for calculating the probability density function (PDF). Finally, the probability of error (P_e) of each detector is compared by extensive Monte-Carlo simulation.