Numerical and Experimental Characterization of LoRa-Based Helmet-to-Unmanned Aerial Vehicle Links on Flat Lands: A Numerical-Statistical Approach to Link Modeling

TL;DR

This study evaluates the communication range of LoRa links between helmet-mounted transceivers and UAVs in search and rescue scenarios, using numerical and experimental methods to model signal fluctuations and localization potential.

Contribution

It introduces a combined numerical-statistical approach to model LoRa link behavior and assesses the impact of wearer posture and UAV altitude on communication range and localization.

Findings

Ground-bounce multipath causes strong fluctuations in received power for standing positions.

Lowering UAV altitude confines fluctuations within 100 m from the target.

Helmet transceiver signals can be detected up to 5 km on flat terrain.

Abstract

The use of the LoRa communication protocol in a new generation of transceivers is attractive for search and rescue(SaR) procedures because they can operate in harsh environmentscovering vast areas while maintaining a low power consumption.The possibility of wearing helmets equipped with LoRa-radiosand installing LoRa transceivers in unmanned aerial vehicles (UAVs) will accelerate the localization of the targets, probably unconscious. In this paper, the achievable communication ranges of such links are theoretically and experimentally evaluated by considering the possible positions of the helmet wearer (standing or lying) on a flat field, representing a simple SaR scenario.Simulations and experimental tests demonstrated that, for the standing position, the ground-bounce multi-path produces strong fluctuations of the received power versus the Tx-Rx distances. Such fluctuations can be kept confined within 100 m from the target by lowering the UAV altitude. Instead, for a more critical lying position, the received power profile is monotonic and nearly insensitive to the posture. For all the considered cases, the signal emitted by the body-worn transceiver can be exploited to localize the helmet wearer based on its strength, and it is theoretically detectable by the UAV radio up to 5 km on flat terrain.