RDNN for Classification and Prediction of Rock or Mine in Underwater Acoustics

Abstract

Mines in the waters are just explosives that detonate upon contact with an object. The underwater submarine must foresee if it will encounter a mine or a rock. Lacking the development of the Ranging Sound Navigation approach, which utilizes particular variables to identify whether a surface or a barrier is made of a mine or rock, finding mines or rocks would have been extremely difficult. In our study, we demonstrate a technique for predicting underwater rocks and mines using SONAR waves. At 60 different angles, SONAR pings are employed to record the various frequencies of submerged objects. To identify whether the object in the ocean is a mine or just a rock, the submarine uses SONAR signals, which transmit sound and receive switchbacks. The mine and rock categories are predicted using the prediction models. To create these prediction models, Supervised Machine Learning Classification methods were employed.