다중 센서 복합체 기반 가우시안 프로세스와 딥러닝을 활용한 해양 데이터 매핑 및선박 위치 추정 기법

This research proposes a novel method for determining the location of vessels using a multi-sensor complex consisting of sound, magnetic, and depth sensors. The goal is to create a reliable and precise system that can overcome the limitations of individual sensors by integrating their data. Gaussian Process Regression (GPR) is employed to interpolate sparse data collected by the multi-sensor system, while a deep learning model based on the Transformer architecture is used to estimate the vessel's position. The system is designed to enhance accuracy and robustness, particularly in noisy marine environments. Our method shows potential for real-time applications in underwater localization, particularly in areas with high noise and interference.