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On the Characterization of Time-Scale Underwater Acoustic Signals Using Matching Pursuit Decomposition

By Nicolas F. Josso, Jun Jason Zhang, Antonia Pap, Cornel Ioana, Jerome I. Mars, Cédric Gervaise and Yann Stéphan

Abstract

Abstract — We investigate a characterization of underwater acoustic signals using extracted time-scale features of the propagation channel model for medium-to-high frequency range. The underwater environment over these frequencies causes multipath and Doppler scale changes on the transmitted signal. This is the result of the time-varying nature of the channel and also due to the relative motion between the transmitter-channel-receiver configuration. As a sparse model is essential for processing applications and for practical use in simulations, we employ the matching pursuit decomposition algorithm to estimate the channel time delay and Doppler scale change model attributes for each propagating path. The proposed signal characterization was validated for sparse channel profiles using real-time data from the BASE07 experiment. I

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.413.5202
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