RaDro: indoor drone tracking using millimeter wave radar
File(s)
Published version
Author(s)
Abdelnasser, Heba
Heggo, Mohammad
Pang, Oscar
Kovac, Mirko
McCann, Julie A
Type
Journal Article
Abstract
Core to drone design is its ability to ascertain its location by utilizing onboard inertial sensors combined with GPS data.
However, GPS is not always reachable, especially in challenging environments such as indoors. This paper proposes RaDro; a
system that leverages millimeter-waves (mmWave) to precisely localize and track drones in indoor environments. Unlike
commonly used alternative technologies, RaDro is cost-effective and can penetrate obstacles, a bonus in non-line-of-sight
(NLoS) scenarios, which enhances its reliability for tracking objects in complex environments. It does this without the need for
tags or anchors to be attached to the drone, achieving 3D tracking with just a single radar point, significantly streamlining the
deployment process. Comprehensive experiments are conducted in different scenarios to evaluate RaDro’s performance. These
include employing different drone models with different sizes to execute a range of aerial manoeuvres across different flight
arenas, each with its own settings and clutter, and encountering various LoS and NLoS scenarios in dynamic environments.
The experiments aimed to assess the capabilities of the system to extract coarse-grained and fine-grained information for
drone detection, motion recognition, and localization. The results showcase precise localization, achieving a 50% reduction in
localization error compared to the conventional baseline. This localization accuracy remains resilient even when confronted
with interference from other moving sources. The results also demonstrate the system’s ability to accurately localize drones
in NLoS scenarios where existing state-of-the-art optical technologies cannot work.
However, GPS is not always reachable, especially in challenging environments such as indoors. This paper proposes RaDro; a
system that leverages millimeter-waves (mmWave) to precisely localize and track drones in indoor environments. Unlike
commonly used alternative technologies, RaDro is cost-effective and can penetrate obstacles, a bonus in non-line-of-sight
(NLoS) scenarios, which enhances its reliability for tracking objects in complex environments. It does this without the need for
tags or anchors to be attached to the drone, achieving 3D tracking with just a single radar point, significantly streamlining the
deployment process. Comprehensive experiments are conducted in different scenarios to evaluate RaDro’s performance. These
include employing different drone models with different sizes to execute a range of aerial manoeuvres across different flight
arenas, each with its own settings and clutter, and encountering various LoS and NLoS scenarios in dynamic environments.
The experiments aimed to assess the capabilities of the system to extract coarse-grained and fine-grained information for
drone detection, motion recognition, and localization. The results showcase precise localization, achieving a 50% reduction in
localization error compared to the conventional baseline. This localization accuracy remains resilient even when confronted
with interference from other moving sources. The results also demonstrate the system’s ability to accurately localize drones
in NLoS scenarios where existing state-of-the-art optical technologies cannot work.
Date Issued
2024-08
Date Acceptance
2024-07-12
Citation
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2024, 8 (3)
ISSN
2474-9567
Publisher
Association for Computing Machinery (ACM)
Journal / Book Title
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Volume
8
Issue
3
Copyright Statement
© 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
This work is licensed under a Creative Commons Attribution International 4.0 License.
License URL
Identifier
https://dl.acm.org/doi/10.1145/3678549
Publication Status
Published
Article Number
88
Date Publish Online
2024-09-09