Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Time-Frequency Modeling of Shallow Water Environments: Rigid vs. Fluid Seabed
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Discrete Time-Frequency Characterizations of Dispersive Linear Time-Varying Systems
IEEE Transactions on Signal Processing
Nonstationary system analysis methods for underwater acoustic communications
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in theory and methods for nonstationary signal analysis
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We investigate a frequency-domain characterization of shallow water environments based on normal-mode models of acoustic mediums. The shallow water environment can be considered as a time-dispersive system whose time-varying impulse response can be expressed as a superposition of time-frequency components with dispersive characteristics. After studying the dispersive characteristics, a blind time-frequency processing technique is employed to separate the normal-mode components without knowledge of the environment parameters. This technique is based on first approximating the time-frequency structure of the received signal and then designing time-frequency separation filters based on warping techniques. Following this method, we develop two types of receivers to exploit the diversity inherent in the shallow water environment model and to improve underwater communication performance. Numerical results demonstrate the dispersive system characterization and the improved processing performance of the receiver structures.