Detection rate statistics in synthetic aperture sonar images

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Abstract
Synthetic aperture sonar (SAS) has proved to be successful for mine hunting andis now robust for generating high-resolution images over wide swath. The subsequent stepin the processing is detection, discriminating between mine-like and non-mine-like objects,which is designed to minimise the number of missed mines so that the system can managethe detection rate. Statistical analysis using SAS has been limited, because operational useof the technology is at an early stage. The design of automated detection and classificationsystems depends however on these statistics, which for a SAS are environment dependent.NURC has collected a comprehensive data set off the coast of Latvia with the MUSCLESAS, which comprises a wide range of seabeds, clutter and vehicle motion. The statisticalanalysis is based on 50 km2 of SAS images at centimetre resolution.
URI
http://hdl.handle.net/20.500.12489/650
Report Number
NURC-PR-2009-002
Source
Originally published in: Proceedings of the 3rd International Conference and Exhibition on Underwater Acoustic Measurements: Technologies and Results, 21-26 June, 2009, Nafplion, Greece.
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Date
2009/12
Author(s)
Groen, Johannes
; 
Coiras, Enrique
; 
Williams, David
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