Development of a Digital Twin of an Autonomous Underwater Vehicle to Assess the Effectiveness of Searching for Bottom Objects

The problem of developing a digital twin of an autonomous underwater vehicle is being solved to assess the effectiveness of its functioning when searching for bottom objects. The factors on which the effectiveness of searching in a given area depends are analyzed, and the processes that need to be reproduced using simulation modeling are identified. It has been determined that the effectiveness of searching for objects depends on the size of the area, the performance of the search determined by the width of the inspection swath, the physical principles of detection means, the bottom topography, and the state of the marine environment. When using the method of statistical tests (Monte Carlo method) to evaluate the effectiveness in each test, simultaneously with the movement of the autonomous underwater vehicle, the following are reproduced: the movement of detection means, characterized by sectors of view, the sequential selection of detection means for searching, determined by the control system of the vehicle depending on environmental conditions and the degree of identification of classification characteristics of the search object.