Interpreting and processing side-scan sonar data with the objective of further automation

One of the most effective tools of remote sensing and visualization of underwater surfaces and objects are acoustic devices, in particular side-scan sonars (SSS). Recently, largely due to the emergence of affordable devices, the geography and scope of application of this device has been significantly expanded. Meanwhile, despite certain progress achieved in terms of improving and minimizing the SSS hardware, the software used remains, in general, at a basic level, providing the operator mainly with a simple tool for visualizing benthic environments and data recording for further post-processing. Existing experience in SSS exploitation reveals that the key issue of interpreting acoustic images lies in the physical essence of their acquisition. Arguably, attempts to implement methods of automated interpretation of optical images have no perspective. Hence, the objective of this paper is to provide a theoretical and practical background of SSS data interpretation and processing. A layout for the potential automation of this process is provided with the objective of eliminating human operation in the process of conducting survey and search operations. The authors consider the conditions of SSS exploitation including special attention to such issues as the vastness of search areas, which, as argued is the key problem of data and data pattern recognition. SSS image recognition is an issue relevant for a wide range of academic topics such as geometric distortion, image recognition, and navigation satellite system target localization.