Compression of Multibeam Echosounders Bathymetry and Water Column Data

Author:

Martí AniolORCID,Portell JordiORCID,Amblas DavidORCID,de Cabrera FerranORCID,Vilà MarcORCID,Riba JaumeORCID,Mitchell GarrettORCID

Abstract

Over the past decade, Multibeam Echosounders (MBES) have become one of the most used techniques in sea exploration. Modern MBES are capable of acquiring both bathymetric information on the seafloor and the reflectivity of the seafloor and water column. Water column imaging MBES surveys acquire significant amounts of data with rates that can exceed several GB/h depending on the ping rate. These large file sizes obtained from recording the full water column backscatter make remote transmission difficult if not prohibitive with current technology and bandwidth limitations. In this paper, we propose an algorithm to decorrelate water column and bathymetry data, focusing on the KMALL format released by Kongsberg Maritime in 2019. The pre-processing stage is integrated into FAPEC, a data compressor originally designed for space missions. Here, we test the algorithm with three different datasets: two of them provided by Kongsberg Maritime and one dataset from the Gulf of Mexico provided by Fugro USA Marine. We show that FAPEC achieves good compression ratios at high speeds using the pre-processing stage proposed in this paper. We also show the advantages of FAPEC over other lossless compressors as well as the quality of the reconstructed water column image after lossy compression at different levels. Lastly, we test the performance of the pre-processing stage, without the constraint of an entropy encoder, by means of the histograms of the original samples and the prediction errors.

Funder

European Regional Development Fund

Institute of Cosmos Sciences University of Barcelona

Spanish State Research Agency

Marie Sklodowska-Curie Actions

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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2. Context-Aware Lossless and Lossy Compression of Radio Frequency Signals;Sensors;2023-03-28

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4. Analysis of Lossless Data Compression Algorithm in Columnar Data Warehouse;2022 6th International Conference On Computing, Communication, Control And Automation (ICCUBEA;2022-08-26

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