  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.
