UACE2017 Proceedings: Towards automated HF sidescan sonar performance estimation

Session:
Towards Automatic Target Recognition. Detection, Classification and Modelling
Paper:
Towards automated HF sidescan sonar performance estimation
Author(s):
Marc Geilhufe, Hauke Voss, Roy Edgar Hansen, Øivind Midtgaard, Stig Asle Vaksvik Synnes, Torstein Olsmo Sæbø
Abstract:
FFI developed the tool "MCM Insite" for Mine Countermeasures (MCM) performance evaluation for Autonomous Underwater Vehicles (AUVs) equipped with side looking sonars. It estimates image quality and image complexity automatically from sonar images. The concept has been successfully applied to different synthetic aperture sonar (SAS) sensor systems taking full advantage of constant spatial resolution and phase information. However, it is more difficult to extract the required image metrics with non-interferometric, high-frequency sidescan sonar (SSS) systems, which are widely used for imaging the seafloor during minehunting operations. The main challenge of assessing image quality with SSS is to find a good signal-to-noise ratio (SNR) estimation from its common beamformed amplitude output. Also, for image complexity, the varying along-track resolution over range imposes a challenge when using scale-based image texture techniques. In this paper we aim for a solution for Edgetech SSS at 850 kHz frequency demonstrated on shallow water data.
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