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Sensors for Unmanned Traffic Management
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Sensors for Unmanned Traffic Management

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 6258

Special Issue Editors

Dr. Juan Alberto Besada Portas

E-Mail Website
Guest Editor
Signals, Systems and Radiocommunications Department, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: UAV traffic management; drone applications; air traffic management; data fusion
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Roberto Sabatini

E-Mail Website
Guest Editor
Department of Aerospace Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates
Interests: aerospace vehicle design and testing; avionics and air traffic management systems; spaceflight systems design and operations; aerospace robotics and autonomous systems; guidance, navigation and control systems; unmanned aircraft systems (UAS) and UAS traffic management; advanced air mobility and urban air mobility; distributed and intelligent satellite systems; space domain awareness and space traffic management; GNSS integrity monitoring and augmentation; defense C4ISR and electronic warfare systems; cognitive human-machine systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, Unmanned Aircraft System (UAS) applications have bloomed, ranging from aerial surveillance to remote infrastructure monitoring, freight delivery, geophysics surveying, and so on. In order to guarantee drone operations safety, UAS Traffic Management (UTM) systems are being developed and progressively introduced into service. They are formed of a collection of distributed pre-flight and real-time traffic coordination services, enabling pilot situation awareness (regarding nearby traffic, weather hazards, obstacles, aerospace limitations, etc.) and separation (both at the strategic and tactical level). Especially for real time/tactical coordination, there is a clear need for accurate and robust sensors both in the unmanned aircraft and on the ground, particularly when operating in critical areas (near airports, densely populated areas, etc.). Those sensors are not only related to UAS positioning, navigation and tracking (e.g., non-cooperative surveillance and anti-drone sensors), but should also contribute to the acquisition of contextual information relevant to UTM, such as weather or communication coverage maps. Additionally, the processing of their measurements, increasingly relying on Artificial Intelligence (AI) techniques, is of paramount importance.

The aim of this Special Issue is to solicit papers from academia and industry researchers with original and innovative works on all aspects of UTM-related sensors and multi-sensor data fusion, which review and report on the state of the art, highlight challenges, and point to future directions.

Dr. Juan Alberto Besada Portas
Prof. Dr. Roberto Sabatini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Robust UAS navigation and surveillance for UTM
  • Ground-based UAS tracking sensors for UTM
  • Meteorologic sensors for UTM
  • CNS performance metrics and assessment for UTM
  • Multisensor data fusion for UTM
  • Flight test, benchmark, and simulation studies in UTM
  • Safety, security and privacy issues in UTM

Published Papers (2 papers)

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Research

29 pages, 6295 KiB  
Article
Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management
by Juan A. Besada, David Carramiñana, Luca Bergesio, Ivan Campaña and Ana M. Bernardos
Sensors 2022, 22(4), 1498; https://doi.org/10.3390/s22041498 - 15 Feb 2022
Cited by 7 | Viewed by 2008
Abstract
Unmanned traffic management (UTM) systems rely on collaborative position reporting to track unmanned aerial system (UAS) operations over wide unsurveilled (with counter-UAS systems) areas. Many different technologies, such as Remote-ID, ADS-B, FLARM, or MLAT might be used for this purpose, in addition to [...] Read more.
Unmanned traffic management (UTM) systems rely on collaborative position reporting to track unmanned aerial system (UAS) operations over wide unsurveilled (with counter-UAS systems) areas. Many different technologies, such as Remote-ID, ADS-B, FLARM, or MLAT might be used for this purpose, in addition to the direct exploitation of C2 telemetry, relayed though cellular networks. This paper provides an overview of the most used collaborative sensors and surveillance systems in this context, analyzing their main technical parameters and performance effects. In addition, this paper proposes an abstracted general statistical simulation model covering message encoding, network capacity and access, sensors coverage and distribution, message transmission and decoding. Making use of this abstracted model, this paper proposes a particularized set of simulation models for ADS-B, FLARM and Remote-Id; it is thus useful to test their potential integration in UTM systems. Finally, a comparative analysis, based on simulation, of these systems, is performed. It is shown that the most relevant effects are those related with quantification and the potential saturation of the communication channels leading to collisions and delays. Full article
(This article belongs to the Special Issue Sensors for Unmanned Traffic Management)
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30 pages, 3790 KiB  
Article
Review and Simulation of Counter-UAS Sensors for Unmanned Traffic Management
by Juan A. Besada, Ivan Campaña, David Carramiñana, Luca Bergesio and Gonzalo de Miguel
Sensors 2022, 22(1), 189; https://doi.org/10.3390/s22010189 - 28 Dec 2021
Cited by 8 | Viewed by 3557
Abstract
Noncollaborative surveillance of airborne UAS (Unmanned Aerial System) is a key enabler to the safe integration of UAS within a UTM (Unmanned Traffic Management) ecosystem. Thus, a wide variety of new sensors (known as Counter-UAS sensors) are being developed to provide real-time UAS [...] Read more.
Noncollaborative surveillance of airborne UAS (Unmanned Aerial System) is a key enabler to the safe integration of UAS within a UTM (Unmanned Traffic Management) ecosystem. Thus, a wide variety of new sensors (known as Counter-UAS sensors) are being developed to provide real-time UAS tracking, ranging from radar, RF analysis and image-based detection to even sound-based sensors. This paper aims to discuss the current state-of-the art technology in this wide variety of sensors (both academically and commercially) and to propose a set of simulation models for them. Thus, the review is focused on identifying the key parameters and processes that allow modeling their performance and operation, which reflect the variety of measurement processes. The resulting simulation models are designed to help evaluate how sensors’ performances affect UTM systems, and specifically the implications in their tracking and tactical services (i.e., tactical conflicts with uncontrolled drones). The simulation models cover probabilistic detection (i.e., false alarms and probability of detection) and measurement errors, considering equipment installation (i.e., monostatic vs. multistatic configurations, passive sensing, etc.). The models were integrated in a UTM simulation platform and simulation results are included in the paper for active radars, passive radars, and acoustic sensors. Full article
(This article belongs to the Special Issue Sensors for Unmanned Traffic Management)
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