F.B. Louza fblouza(at)ualg.pt
S.M. Jesus sjesus(at)ualg.pt
LarSys, Universidade do Algarve, Campus de Gambelas, PT-8005-139 Faro, Portugal.
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Ref.: in Proceedings of Meetings on Acoustics (POMA), Vol.44(1), 070011, October 2021.
This paper presents a double Wiener superimposed training method for low SNR communications. Research on the field has been encouraged, in recent years, to keep underwater vehicles undetected while communicating, as well as to mitigate the impacts of acoustic signals over marine life. In this approach, several consecutive low power broadband bit streams composed of a long probe superimposed to the message are recorded on a four-hydrophone pyramidal array. The method uses a classic minimum mean square error (MMSE) Wiener filter for equalization. To explore temporal diversity, a fast Hadamard transform (FHT) estimates the channel impulse response for time synchronization of each MMSE filtered bit stream. For each channel, a coherent averaging of several time- aligned signals results in an error-corrected averaged signal. A second Wiener filter is then applied over the time-averaged sequence to remove residual intersymbol interference. A spatial combination of the four time-averaged bit streams, from each channel, is performed. A method called “Hyperslice Cancellation by Coordinate Zeroing” removes the intentional probe interference, and the original message is recovered. To prove the concept, a small subset of data collected during the experiment BioCom’19 was used. The short-range experiment was performed in a shallow-water site, in Cabo Frio Island bay, a challenging environment due to the upwelling that rapidly modifies the ocean temperature stratification, degrading the acoustic propagation. Despite BER fluctuation in time, the system proved robust, dealing with these short time scale signal fluctuations and high noise levels that hamper efforts to recover the message. To evaluate the performance for a single unit and an array, the four channels were processed independently and coherently combined. Compared to a previous method based on a single Wiener, the double Wiener approach achieved better performance, providing a mean square error gain up to 4.7 dB.