Automatic discrimination of underwater acoustic signals generated by teleseismic P-waves: A probabilistic approach

Abstract

We propose a new probabilistic scheme for the automatic recognition of underwater acoustic signals generated by teleseismic P‐waves recorded by hydrophones in the ocean. The recognition of a given signal is based on the relative distribution of its power among different frequency bands. The signal's power distribution is compared with a statistical model developed by analyzing relative power distributions of many signals of the same origin and a numerical criterion is calculated, which can serve as a measure of the probability for the signal to belong to the statistical model. Our recognition scheme was applied to 6‐month‐long continuous records of seven ocean bottom hydrophones (OBH) deployed in the Ligurian Sea. A maximum of 94% of all detectable teleseismic P‐waves recorded during the deployment of the OBHs were recognized correctly with no false recognitions. The proposed recognition method will be implemented in autonomous underwater robots dedicated to detect and transmit acoustic signals generated by teleseismic P‐waves.

Automatic recognition of T and teleseismic P waves by statistical analysis of their spectra: An application to continuous records of moored hydrophones

“…The spectral power distribution as a function of a frequency band is estimated with the help of the discrete wavelet transform (DWT), similar to the procedure described by Sukhovich et al []. For the sake of completeness, we provide here a brief description.…”

“…We use a biorthogonal wavelet basis with two and four vanishing moments for the primal and dual wavelets, respectively, which is commonly abbreviated as CDF(2,4) [ Cohen et al , ]. As was shown previously [ McGuire et al , ; Sukhovich et al , ], this wavelet construction provides a good compromise between computational effort and the filtering performance of the wavelets.…”

“…Matsumoto et al [] have proposed a simple algorithm to perform an automatic detection of T waves by autonomous underwater robots. Recently, Sukhovich et al [] have developed a probabilistic method for use on similar floats dedicated to record acoustic signals generated by teleseismic P waves [ Simons et al , ; Hello et al , ]. While showing promising results, these methods are not quite universal as they require separate tailoring of their parameters for the detection of signals of a given type.…”

“…Combined for all trees, this information allows one to calculate, for example, the effect of a single discriminating variable or the joint effect of several variables. Similar to the method of Sukhovich et al [], our method uses the information on the distribution of the signal spectral power among different frequency bands; in contrast to Sukhovich et al [], the use of Gradient Boosted Decision Trees (GBDT) allows classification of several signal types simultaneously . We have applied the new method to the data recorded by two moored hydrophones of the Seismic Investigation by REcording of Acoustic Waves in the North Atlantic (SIRENA) network which operated during the years 2002 and 2003 [ Goslin et al , ].…”

Modern mermaids: New floats image the deep Earth

“…In a future operational phase the floats will remain at large, surfacing only when a strong P wave is recorded. The command to surface is triggered by a discrimination algorithm developed by Sukhovich et al [2011]; once surfaced, the instrument transmits the stored seismograms via satellite before returning to its floating depth.…”