%0 Conference Paper %F Oral %T Blind Separation of Underwater Acoustic Signals %+ Lab-STICC_ENSTAB_CACS_COM %+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) %+ Ecole Nationale Supérieure des Ingénieurs des Etudes et Techniques d'Armement (Ensieta) %A Mansour, Ali %A Nabih, Benchekroun %A Gervaise, Cedric %< avec comité de lecture %B Independent Component Analysis and Blind source Separation, Lecture Notes in Computer Science 3889 %C Charleston, United States %8 2006 %D 2006 %Z Computer Science [cs]/Signal and Image Processing %Z Engineering Sciences [physics]/Signal and Image processingConference papers %X In last two decades, many researchers have been involved in acoustic tomography applications. Recently, few algorithms have been dedicated to the passive acoustic tomography applications in a single input single output channel. Unfortunately, most of these algorithms can not be applied in a real situation when we have a Multi-Input Multi-Output channel. In this paper, we propose at first a realistic model of an underwater acoustic channel, then a general structure to separate acoustic signals crossing an underwater channel is proposed. Concerning ICA algorithms, many algorithms have been implemented and tested but only two algorithms give us good results. The latter algorithms minimize two different second order statistic criteria in the frequency domain. Finally, some simulations have been presented and discussed. KEY WORD: Underwater acoustic applications, passive acoustic Tomography, second order statistics in frequency domain, multipath channel, sparseness or non-stationary signals. %G English %L hal-00802832 %U https://hal.science/hal-00802832 %~ UNIV-BREST %~ INSTITUT-TELECOM %~ ENSTA-BRETAGNE %~ CNRS %~ UNIV-UBS %~ ENSTA-BRETAGNE-STIC %~ ENIB %~ LAB-STICC_ENIB %~ LAB-STICC %~ INSTITUTS-TELECOM