Intelligent Decision Support System for Detection of Anomalies and Unmanned Surface Vehicle Inertial Navigation Correction

Abstract

The paper presents a monitoring system based on a distributed network of autonomous surface robots for automated comprehensive monitoring of water parameters across the observed field. It proposes an intelligent decision support system for anomalies detection that enables high-awareness expert decision-making in terms of factor space of the scalar and vector fields, increase the sufficiency, accuracy, and reliability. The authors present a solution to the problem of correcting the readings from the robot control system; the solution is based on inertial MEMS sensors and nonlinear filtration. The developed hardware and software were used to carry out computational experiments to optimize the system scenarios and further optimize the controls in real time.