Proc. IEEE Asilomar Conference on Signals, Systems and Computers, November 2-5, 2014, Pacific Grove, California USA.

Sonar Data Compression Using Non-Uniform Quantization and Noise Shaping

Lok S. Wong, Gregory E. Allen and Brian L. Evans

Advanced Technology Laboratory, Applied Research Laboratories, The University of Texas at Austin, Austin, TX 78712 USA - -

Paper Draft - Poster Presentation

Underwater Acoustic Communication Datasets


Sonar sensor arrays potentially produce huge amounts of data to be recorded or transmitted over a telemetry system. Compression can reduce the required storage or transmission bandwidth, or allow a larger or higher fidelity array. We use a dataset for a sonar array receiving acoustic communication signals from a transmitter in a lake test. We compress the received signals to evaluate the effect of compression on performance. Based on analysis of the dataset, we use non-uniform quantization with a Laplace distribution along with noise-shaped feedback coding. We demonstrate that this sonar data can be compressed from 16-bit to five-bit values with little or no change in performance using our technique.

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Last Updated 11/19/14.