Abstract
Frequency shift keyed acoustic signals transmitted in underwater sensor networks are affected by numerous factors such as ambient noise, ocean interference, and other random sources which make them nonlinear and non-stationary in nature. In recent years, the use of empirical mode decomposition (EMD) technique to analyze modulated acoustic signals has gained importance. In this paper, an EMD-based approach is proposed to extract frequency shift keying (FSK)-modulated acoustic stationary signals in the underwater channel that are affected by above-mentioned factors in shallow water over a range of 100 Hz to 10 kHz. EMD is an experimental technique which decomposes a signal into a set of oscillatory modes known as intrinsic mode functions (IMF). The proposed algorithm makes use of FFT for the identification and extraction of oscillatory signal. To validate the proposed algorithm, computer simulation is carried out by exploiting the real-time data perturbed by ambient noises. It is observed from the simulation results that the proposed EMD approach identifies and extracts two FSK stationary signals against various ambient noises present in the channels of the underwater sensor network.
Published Version
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