Volume 126, Issue 6, December 2009
Index of content:
- UNDERWATER SOUND 
126(2009); http://dx.doi.org/10.1121/1.3242374View Description Hide Description
Measurements are presented from a multi-frequency acoustic backscatter study of aqueous suspensions of irregularly shaped quartz sediments having broad particle size distributions. Using the backscattered sound from a homogenous suspension,measurements of the ensemble backscatter form function and ensemble normalized total scattering cross section were obtained. Three different size distribution types are examined; namely Gaussian, log-normal, and bi-modal distributions, each covering a range of particle sizes similar to those observed in sandy marine environments near the seabed. The measurements of ensemble scattering are compared with theoretical predictions, derived by integrating the intrinsic scatteringproperties of the sediments over the probability density functions of the size distributions used in the present study. The results show that the ensemble scattering parameters are significant functions of both the width and type of size distribution in suspension. The impact of errors in size distribution width on inversion predictions of both mean size and suspended concentration is also examined. The validity of the theoretical predictions is discussed, along with the implication of the inversion results for using acoustic backscatter data to measure suspended concentration and particle size in sandy marine environments.
126(2009); http://dx.doi.org/10.1121/1.3257588View Description Hide Description
Monitoring blue and fin whales summering in the St. Lawrence Estuary with passive acoustics requires call recognition algorithms that can cope with the heavy shipping noise of the St. Lawrence Seaway and with multipath propagation characteristics that generate overlapping copies of the calls. In this paper, the performance of three time-frequency methods aiming at such automatic detection and classification is tested on more than 2000 calls and compared at several levels of signal-to-noise ratio using typical recordings collected in this area. For all methods, image processing techniques are used to reduce the noise in the spectrogram. The first approach consists in matching the spectrogram with binary time-frequency templates of the calls (coincidence of spectrograms). The second approach is based on the extraction of the frequency contours of the calls and their classification using dynamic time warping (DTW) and the vector quantization (VQ) algorithms. The coincidence of spectrograms was the fastest method and performed better for blue whale A and B calls. VQ detected more 20 Hz fin whale calls but with a higher false alarm rate. DTW and VQ outperformed for the more variable blue whale D calls.