Automatic detection of bioacoustics impulses based on kurtosis under weak signal to noise ratio

Abstract

Passive acoustic monitoring (PAM) of marine mammal vocalizations has been efficiently used in a wide set of applications ranging from marine wildlife surveys to risk mitigation of military sonar emissions. The primary use of PAM is for detecting bioemissions, a good proportion of which are impulse sounds or clicks. A click detection algorithm based on kurtosis estimation is proposed as a general automatic click detector. The detector works under the assumption that click trains are embedded in stochastic but Gaussian noise. Under this assumption, kurtosis is used as a statistical test for detection. The algorithm explores acoustic sequences with the optimal frequency bandwidth for focusing on impulse sounds. The detector is successfully applied to field observations, and operates under weak signal to noise ratios and in presence of stochastic background noise. The algorithm adapts to varying click center frequency. Kurtosis appears as a promising approach to detect click trains, alone or in combination with other clicks detector, and to isolate individual clicks.