Automated Chirp Detection with Diffusion Entropy: Application to Infrasound from Sprites

Abstract

We study the performance of three different methods to automatically detect a chirp in background noise. (1) The standard deviation detector uses the computation of the signal to noise ratio. (2) The spectral covariance detector is based on the recognition of the chirp in the spectrogram. (3) The CASSANDRA detector uses diffusion entropy analysis to detect periodic patterns in noise. All three detectors are applied to an infrasound recording for detecting chirps produced by sprites. The CASSANDRA detector provides the best trade off between the false alarm rate and the detection efficiency.