High-Resolution Underwater Mapping Using Side-Scan Sonar

Abstract

The goal of this study is to generate high-resolution sea floor maps using a Side-Scan Sonar(SSS). This is achieved by explicitly taking into account the SSS operation as follows. First, the raw sensor data is corrected by means of a physics-based SSS model. Second, the data is projected to the sea-floor. The errors involved in this projection are thoroughfully analysed. Third, a probabilistic SSS model is defined and used to estimate the probability of each sea-floor region to be observed. This probabilistic information is then used to weight the contribution of each SSS measurement to the map. Because of these models, arbitrary map resolutions can be achieved, even beyond the sensor resolution. Finally, a geometric map building method is presented and combined with the probabilistic approach. The resulting map is composed of two layers. The echo intensity layer holds the most likely echo intensities at each point in the sea-floor. The probabilistic layer contains information about how confident can the user or the higher control layers be about the echo intensity layer data. Experimental results have been conducted in a large subsea region.

Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar

“…Drawing upon the technical literature on sidescan image processing (e.g. Reed and Hussong, 1989;Cervenka and De Moustier, 1993;Collier and Brown, 2005;Burguera and Oliver, 2016) the present contribution details the algorithms, assumptions, and structure of a freely available, open-source software designed for ease of use by the nonacoustician.…”

“…ping-to-ping and pixel-to-pixel) and horizontal. This is a standard assumption in processing sidescan data because co-located bathymetric information is usually not available, and because when the terrain roughness is small compared to the sonar altitude (height above the bed), the errors are small, as shown by Burguera and Oliver (2016).…”

“…Following Burguera and Oliver (2016), the echo intensity S [m, n] returned by a point on the bed p = (r[m] , θ s ) is modeled as:…”

A New Radiometric Correction Method for Side-Scan Sonar Images in Consideration of Seabed Sediment Variation

“…However, the specific approach to sediment classification proposed in this study is not crucial, and others with equal effectiveness could be used. Many other side-scan sediment classification approaches are discussed in related literature, such as those proposed by Buscombe et al [25] and Burguera and Oliver [17], in which each pixel is classified into one of several discrete classes. Several sediment classification approaches work better than others in specific environments.…”

“…However, TVG cannot always accurately compensate for transmission losses in applications due to the use of improper or empirical parameters, so radiometric distortion induced by TVG residuals appears in SSS images. The approaches of correcting beam patterns range from simple models of Lambertian scattering [16] to complex models of sonar sensitivity that are contingent on sonar aperture, frequency, and transducer dimensions [7,17]. The effects of beam pattern and angular response can also be regarded as angular and can be compensated for by identifying proper angle-BS curves [9,10,14,15].…”