On the application of the Bayesian search method for detecting underwater objects

Underwater archaeology and, in particular, the study of shipwrecked vessels, is one of the most advanced fields in the discipline, covering a range of theoretical and applied problems. In the practice of searching for sunken ships, it is quite rare to find a ship on the basis of previously (a priori) known data. In this regard, as well as in connection with the use of definitions from the field of probability theory and mathematical statistics, Bayesian statistics, namely, a search method that has found application in a number of well-known international search projects, has become the natural direction for the development of search systems. The Bayesian search method for determining the location of sunken ships, as well as their identification, has been almost never used in domestic underwater archeology practice. However, there is a need for its use, as it was demonstrated by the 2024 expedition to search for the transport ship Tbilisi, sunk during the Great Patriotic War in the Yenisei Gulf: despite the relatively small area of the search zone, determining the ship’s location became a very labor-intensive process. At the same time, the use of Bayesian search could significantly simplify this task. In this regard, the paper examines the methodology of using Bayesian search to detect sunken ships (an example of constructing a probability distribution in the search zone of the ship Tbilisi is given). In addition, the author considered the issue of using the Bayesian method for identifying objects (a database model is proposed with the inclusion of various search parameters). As a real example, the results of the 2024 expedition are presented with a description of the historical object, search conditions, and problems that arose during this work.