Citation: Güzey, N. RF Source
Localization Using Multiple UAVs
through a Novel Geometrical RSSI
Approach. Drones 2022, 6, 417.
https://doi.org/10.3390/
drones6120417
Academic Editors: Andrzej
Łukaszewicz, Wojciech Giernacki,
Zbigniew Kulesza, Jaroslaw Pytka
and Andriy Holovatyy
Received: 9 November 2022
Accepted: 12 December 2022
Published: 15 December 2022
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Article
RF Source Localization Using Multiple UAVs through a Novel
Geometrical RSSI Approach
Nurbanu Güzey
Department of Electrical-Electronics Engineering, Sivas University of Science and Technology,
Sivas 58000, Turkey; nurbanu.guzey@sivas.edu.tr
Abstract:
In this paper, a novel geometrical localization scheme based on the Received Signal Strength
Indicator (RSSI) is developed for a group of unmanned aerial vehicles (UAVs). Since RSSI-based
localization does not require complicated hardware, it is the correct choice for RF target localization.
In this promising work, unlike the other techniques given in the literature, transmit power or path
loss exponent information is not needed. The procedure depends on the received power difference of
each receiver in UAVs. In the developed scheme, four UAVs forming two groups fly in perpendicular
planes. Each UAV in the group moves in a circle, keeping its distance from the plane’s center until
it gets equal power with the other members of its group. Using this movement rate, lines passing
through the source position are calculated. The intersection of these lines gives the position of the
RF target. However, in a noisy environment, the lines do not intersect at one point. Therefore,
the algorithm given in the manuscript finds a point that has a minimum distance to all lines and
is also developed. Simulation results are provided at the end of the manuscript to verify our
theoretical claims.
Keywords: localization; received signal strength indicator; unmanned aerial vehicles
1. Introduction
Unmanned Aerial Vehicles (UAVs) and other new smartly linked platforms have
become increasingly integrated into the Internet of Things, which is a vast global network
(IoT). UAVs not only provide a practical solution to the drawbacks of fixed terrestrial IoT
infrastructure, but also new ways to supply value-added IoT services through a variety of
applications ranging from monitoring and surveillance to on-demand last-mile deliveries
and people transport. UAVs are predicted to soon be a vital component of our cities and
rule the common low-altitude airspace if they live up to their potential [1].
Localization and tracking are crucial issues to be solved in commercial and military
applications such as air traffic control, remote sensing, and intelligence, surveillance, and
reconnaissance (ISR) [
2
]. Initially, ground-based methods were used to conduct localization.
However, due to the fast development of UAVs and sensor technology, UAVs are now able
to be used as airborne sensing devices. Furthermore, some applications, such as search
and rescue missions, may require only aerial localization. The aerial vehicles’ mobility and
extensive eyesight allow for successful and fast localization. Furthermore, flying above
ground level decreases signal propagation uncertainty due to obstacles and enhances RF
target identification. However, when the UAV wanted to follow a trajectory to track a
target, a control methodology was required. In [
3
], a vector-field method is proposed that
does not require knowledge of course dynamics or wind. In [
4
,
5
], an autopilot control
system is proposed.
Apart from search, rescue, and surveillance operations, UAVs are also used in smart
city applications where high technologies such as IoT and deep learning are used. In [
6
], it
is recommended to use computer vision and deep learning techniques in UAVs to improve
the quality of life of visually impaired individuals. UAVs are also used to detect, locate,
Drones 2022, 6, 417. https://doi.org/10.3390/drones6120417 https://www.mdpi.com/journal/drones
