Acoustic detection of North Atlantic right whale contact calls using spectrogram-based statistics

In the presence of impulsive noise, the spectrogram-based detector using the French hat wavelet as the filter kernel outperforms the GLRT detector and decreases computational time by a factor of 6.

Abstract

This paper considers the problem of detection of contact calls produced by the critically endangered North Atlantic right whale, Eubalaena glacialis. To reduce computational time, the class of acceptable detectors is constrained by the detectors implemented as a bank of two-dimensional linear FIR filters and using the data spectrogram as the input. The closed form representations for the detectors are derived and the detection performance is compared with that of the generalized likelihood ratio test (GLRT) detector. The test results demonstrate that in the presence of impulsive noise, the spectrogram-based detector using the French hat wavelet as the filter kernel outperforms the GLRT detector and decreases computational time by a factor of 6.