2019_programme: ENHANCED SONAR IMAGE RESOLUTION USING COMPRESSIVE SENSING MODELLING

• Session: 24. Inversion methods in underwater acoustics
  Organiser(s): N/A
• Lecture: ENHANCED SONAR IMAGE RESOLUTION USING COMPRESSIVE SENSING MODELLING
  Paper ID: 868
  Author(s): Gällström Andreas, Fuchs Louise, Larsson Christer
  Presenter: Gällström Andreas
  Presentation type: oral
  Abstract: 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) 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 also the different autofocus techniques in general require overlapping collected data. This limits the acquisition speed for covering a specific area. \nWe investigate the possibility to enhance the resolution in images processed from one ping measurement. This is done using compressive sensing methods. \nA 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 the formulation of the inverse problem. 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.\nThe 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.\nWe present results based on CS on measurements collected at Saab Dynamics. The measurements are collected using the experimental platform Sapphires in freshwater Lake Vättern. Images processed using classical back projection algorithms are compared to sonar images with enhanced resolution using CS, with a 10 times improvement in cross range resolution. Applications - such as SAS, target classification, 3d imaging and improved methods for autofocus - that can benefit from these results are discussed.
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• Corresponding author: Dr Gällström Andreas
  Affiliation: Saab
  Country: Sweden
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