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Enhanced sonar image resolution using compressive sensing modelling
Saab AB, SE-581 88 Linköping, Sweden ; Department of Electrical and Information Technology, Lund University.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligenta system, Robotics, Perception and Learning, RPL. Saab AB, SE-581 88 Linköping, Sweden.
Saab AB, SE-581 88 Linköping, Sweden ; Department of Electrical and Information Technology, Lund University.
2019 (English)In: Conference Proceedings 5th Underwater Acoustics Conference and Exhibition UACE2019 / [ed] John S. Papadakis, UACE , 2019, p. 995-999Conference paper, Published paper (Other academic)
Abstract [en]

The sonar image resolution is classically limited by the sonar array dimensions. There are several techniques to enhance the resolution; most common is the synthetic aperture sonar (SAS) technique where several pings are added coherently to achieve a longer array and thereby higher cross range resolution. This leads to high requirements on navigation accuracy, but the different autofocus techniques in general also require collecting overlapping data. This limits the acquisition speed whencovering a specific area. We investigate the possibility to enhance the resolution in images processed from one ping measurementin this paperusing compressive sensing methods. A model consisting of isotropic point scatterers is used for the imaged target. The point scatterer amplitudes are frequency and angle independent. We assume only direct paths between the scatterers and the transmitter/receiver in theinverse problemformulation. The solution to this system of equations turns out to be naturally sparse, i.e., relatively few scatterers are required to describe the measured signal.The sparsity means that L1 optimization and methods from compressive sensing (CS) can be used to solve the inverse problem efficiently. We use the basis pursuit denoise algorithm (BPDN) as implemented in the SPGL1 package to solve the optimization problem.We present results based on CS on measurements collected at Saab. The measurements are collected using the experimental platform Sapphires in freshwater Lake Vättern. Images processed using classical back projection algorithms are compared tosonar images with enhanced resolution using CS, with a 10 times improvement in cross range resolution.

Place, publisher, year, edition, pages
UACE , 2019. p. 995-999
Series
Underwater Acoustics Conference and Exhibition, ISSN 2408-0195
Keywords [en]
Sonar, imaging, resolution, Compressive Sensing, Synthetic Aperture Sonar
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-263734OAI: oai:DiVA.org:kth-263734DiVA, id: diva2:1369291
Conference
5th Underwater Acoustics Conference & Exhibition (UACE), Hersonissos, Crete, Greece, 30 Jun - 5 Jul 2019
Note

QC 20191112

Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-11-12Bibliographically approved

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