DisBeaNet: A Deep Neural Network to augment Unmanned Surface Vessels for maritime situational awareness

TL;DR

DisBeaNet is a deep neural network designed for USVs to passively detect, track, and estimate the position of vessels using onboard cameras, enhancing maritime situational awareness without relying on RF-based systems.

Contribution

The paper introduces a novel low-cost vision perception system, DisBeaNet, that enables passive vessel detection and tracking using deep learning, addressing vulnerabilities of RF-based systems in contested environments.

Findings

DisBeaNet accurately detects vessels in maritime scenes.

It estimates vessel distance and bearing from monocular images.

The system can determine vessel latitude and longitude.

Abstract

Intelligent detection and tracking of the vessels on the sea play a significant role in conducting traffic avoidance in unmanned surface vessels(USV). Current traffic avoidance software relies mainly on Automated Identification System (AIS) and radar to track other vessels to avoid collisions and acts as a typical perception system to detect targets. However, in a contested environment, emitting radar energy also presents the vulnerability to detection by adversaries. Deactivating these Radiofrequency transmitting sources will increase the threat of detection and degrade the USV's ability to monitor shipping traffic in the vicinity. Therefore, an intelligent visual perception system based on an onboard camera with passive sensing capabilities that aims to assist USV in addressing this problem is presented in this paper. This paper will present a novel low-cost vision perception system for detecting and tracking vessels in the maritime environment. This novel low-cost vision perception system is introduced using the deep learning framework. A neural network, DisBeaNet, can detect vessels, track, and estimate the vessel's distance and bearing from the monocular camera. The outputs obtained from this neural network are used to determine the latitude and longitude of the identified vessel.