%0 Conference Proceedings %T Signal analysis approach for passive tomography : applications for dispersive channels and moving configuration %+ GIPSA - Signal Images Physique (GIPSA-SIGMAPHY) %+ Développement des Technologies Nouvelles (DTN) %+ Service Hydrographique et Océanographique de la Marine (SHOM) %A Ioana, Cornel %A Josso, Nicolas %A Gervaise, Cedric %A Mars, Jerome, I. %A Stéphan, Yann %< avec comité de lecture %Z Département Images et Signal %( Proceedings of UAM'09 %B UAM 2009 - 3rd international conference and exhibition on Underwater Acoustic Measurements: Technologies and Results %C Napflion, Greece %P - %8 2009-06-21 %D 2009 %K motion effect %K -frequency analysis %K passive tomography %K dispersive channels %Z Computer Science [cs]/Signal and Image Processing %Z Engineering Sciences [physics]/Signal and Image processingConference papers %X Underwater channel is an example of a natural environment potentially characterized by signals generated by various sources : underwater mammals, human activity noise, etc. In order to take advantage of these sources, the concept of passive acoustic tomography has been introduced. According to this concept, the environment parameters could be extracted from the analysis of the received signals. While the signal's parameters are intimately related to physical parameters of the environment, their accurate extraction is crucial. That is, this task is complex while we work in completely passive context and when we deal with a large diversity of underwater signals. Generally, signals issued from underwater environment have complex time-frequency structures : non-linear time-frequency and multi-components. Two typical non-linearities are generated by the dispersive systems and the relative motion between transmitter and receiver. Despite the origin of these phenomena, the signal approach proposed in this paper will provide a unique framework for parameters extraction. This approach is based on the time-frequency-phase coherence of any natural non-linear time-frequency component. Taking advantage of this coherence, the non-linear structures can be efficiently extracted and used for physical parameters estimation. %G English %Z MODE %2 https://hal.science/hal-00455308/document %2 https://hal.science/hal-00455308/file/15-8.pdf %L hal-00455308 %U https://hal.science/hal-00455308 %~ ENSTA-BRETAGNE %~ UGA %~ CNRS %~ UNIV-GRENOBLE1 %~ UNIV-PMF_GRENOBLE %~ UNIV-GRENOBLE3 %~ INPG %~ OSUG %~ GIPSA %~ GIPSA-DIS %~ GIPSA-SIGMAPHY %~ ENSTA-BRETAGNE-STIC %~ ENSIETA-DTN %~ UGA-TEST-BIS %~ UGA-TEST-TER %~ UGA-TEST-QUATER %~ CMM