RF Signal Source Search and Localization Using an Autonomous UAV with Predefined Waypoints

TL;DR

This paper explores UAV-based RF source localization using predefined waypoints, proposing five LLS algorithms to improve real-time and long-term accuracy while considering UAV flight constraints.

Contribution

It introduces five novel LLS-based localization algorithms optimized for UAV navigation with predefined waypoints, balancing accuracy and computational efficiency.

Findings

LLS algorithms achieve high localization accuracy

Predefined waypoints reduce UAV flight distance

Algorithms demonstrate reliable real-time and long-term performance

Abstract

Localization of a radio frequency (RF) signal source has various use cases, ranging from search and rescue, identification and deactivation of jammers, and tracking hostile activity near borders or on the battlefield. The use of unmanned aerial vehicles (UAVs) for signal source search and localization (SSSL) can have significant advantages when compared to terrestrial-based approaches, due to the ease of capturing RF signals at higher altitudes and the autonomous 3D navigation capabilities of UAVs. However, the limited flight duration of UAVs due to battery constraints, as well as limited computational resources on board of lightweight UAVs introduce challenges for SSSL. In this paper, we study various SSSL techniques using a UAV with predefined waypoints. A linear least square (LLS) based localization scheme is considered with enhanced reference selection due to its relatively lower computational complexity. Five different LLS localization algorithms are proposed and studied for selecting anchor positions to be used for localization as the UAV navigates through an area. The performance of each algorithm is measured in two ways: 1) real-time positioning accuracy during the ongoing UAV flight, and 2) long-term accuracy measured at the end of the UAV flight. We compare and analyze the performance of the proposed approaches using computer simulations in terms of accuracy, UAV flight distance, and reliability.