A Search Strategy and Vessel Detection in Maritime Environment Using Fixed-Wing UAVs

TL;DR

This paper presents autonomous search strategies and vessel detection techniques for fixed-wing UAVs operating in GNSS-denied maritime environments, demonstrating effective detection through simulation-based experiments.

Contribution

It introduces both informed and non-informed search methods and a vessel detection algorithm trained on synthetic data for UAVs in challenging maritime scenarios.

Findings

Successful vessel detection in simulation environments

Effective search strategies for GNSS-denied conditions

Combination of sensors and algorithms improves detection reliability

Abstract

In this paper, we address the problem of autonomous search and vessel detection in an unknown GNSS-denied maritime environment with fixed-wing UAVs. The main challenge in such environments with limited localization, communication range, and the total number of UAVs and sensors is to implement an appropriate search strategy so that a target vessel can be detected as soon as possible. Thus we present informed and non-informed methods used to search the environment. The informed method relies on an obtained probabilistic map, while the non-informed method navigates the UAVs along predefined paths computed with respect to the environment. The vessel detection method is trained on synthetic data collected in the simulator with data annotation tools. Comparative experiments in simulation have shown that our combination of sensors, search methods and a vessel detection algorithm leads to a successful search for the target vessel in such challenging environments.