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Special Issue "Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles"

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

Deadline for manuscript submissions: 20 August 2019

Special Issue Editors

Guest Editor
Dr. Elena Simona Lohan

Electrical Engineering unit, Tampere University, Korkeakoulunkatu 1, 33720 Tampere, Finland
Website | E-Mail
Interests: wireless positioning and navigation; 5G; wearable computing; statistical signal processing; IoT
Guest Editor
Dr. Fabio Dovis

Department of Electronics and Telecommunications, Politecnico di Torino, Italy
Website | E-Mail
Interests: GNSS receivers; advanced signal processing for GNSS; detection and mitigation of GNSS interference
Guest Editor
Dr. Alberto De la Fuente

Product Manager at GMV, Madrid, Spain
Website | E-Mail
Interests: GNSS; aviation; localization of GNSS interferences
Guest Editor
Dr. Pau Closas

Department of Electrical & Computing Engineering, Northeastern University, Boston, MA, USA
Website | E-Mail
Interests: statistical and array signal processing; Bayesian inference; GNSS and indoor technologies

Special Issue Information

Dear Colleagues,

Sensors welcomes submissions to this Special Issue on “Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles”.

Commercial and non-commercial aircrafts, and emerging Unmanned Aerial Vehicles (UAVs) of the future, highly rely on GNSS for positioning, navigation and tracking.  However, GNSS is more and more affected by various sources of radiofrequency interference, as pointed out annually by the Eurocontrol voluntary ATM incident report and in the International Air Transport Association (IATA) safety reports. Jamming, spoofing, meaconing, and harmonics from other wireless systems using frequency bands close to GNSS bands, and other types of in-band and adjacent band emissions, are a few examples of possible interferences in GNSS-based localization, navigation, and tracking of aircrafts. Such interferences might threaten drone functionality, with severe concerns for navigation systems, and, as a consequence, in some cases for the safety of users, as well as for the reliability of applications. This call invites original contributions and comprehensive survey papers in research areas related to how to detect, localize, classify and mitigate interference in GNSS signals used in aviation, as well as proposals of alternative or complementary solutions to deal with GNSS interference.

The main themes and keywords to guide potential authors are as follows:

  1. Interference detection, classification, mitigation, and localization in GNSS
  2. Authentication mechanisms in GNSS
  3. Novel navigation solutions for aerial vehicles

Dr. Elena Simona Lohan
Dr. Fabio Dovis
Dr. Alberto de la Fuente
Dr. Pau Closas
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 papers will be 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 1800 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

  • GNSS interferences
  • Spoofing
  • Meaconing
  • Interference detection
  • Interference mitigation
  • Interference localization
  • Interference classification
  • Authentication mechanisms in GNSS
  • Alternative/complementary tracking and navigation methods for aviation
  • Drones
  • Aviation
  • UAV

Published Papers (4 papers)

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Research

Open AccessArticle Impact Analysis of Standardized GNSS Receiver Testing against Real-World Interferences Detected at Live Monitoring Sites
Sensors 2019, 19(6), 1276; https://doi.org/10.3390/s19061276
Received: 24 January 2019 / Revised: 1 March 2019 / Accepted: 5 March 2019 / Published: 13 March 2019
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Abstract
GNSS-based applications are susceptible to different threats, including radio frequency interference. Ensuring that the new applications can be validated against the latest threats supports the wider adoption and success of GNSS in higher value markets. Therefore, the availability of standardized GNSS receiver testing [...] Read more.
GNSS-based applications are susceptible to different threats, including radio frequency interference. Ensuring that the new applications can be validated against the latest threats supports the wider adoption and success of GNSS in higher value markets. Therefore, the availability of standardized GNSS receiver testing procedures is central to developing the next generation of receiver technologies. The EU Horizon2020 research project STRIKE3 (Standardization of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation) proposed standardized test procedures to validate different categories of receivers against real-world interferences, detected at different monitoring sites. This paper describes the recorded interference signatures, their use in standardized test procedures, and analyzes the result for two categories of receivers, namely mass-market and professional grade. The result analysis in terms of well-defined receiver key performance indicators showed that performance of both receiver categories was degraded by the selected interference threats, although there was considerable difference in degree and nature of their impact. Full article
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Open AccessArticle Detection of Induced GNSS Spoofing Using S-Curve-Bias
Sensors 2019, 19(4), 922; https://doi.org/10.3390/s19040922
Received: 16 January 2019 / Revised: 18 February 2019 / Accepted: 18 February 2019 / Published: 22 February 2019
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Abstract
In Global Navigation Satellite System (GNSS), a spoofing attack consists of forged signals which possibly cause the attacked receivers to deduce a false position, a false clock, or both. In contrast to simplistic spoofing, the induced spoofing captures the victim tracking loops by [...] Read more.
In Global Navigation Satellite System (GNSS), a spoofing attack consists of forged signals which possibly cause the attacked receivers to deduce a false position, a false clock, or both. In contrast to simplistic spoofing, the induced spoofing captures the victim tracking loops by gradually adjusting it’s parameters, e.g., code phase and power. Then the victims smoothly deviates from the correct position or timing. Therefore, it is more difficult to detect the induced spoofing than the simplistic one. In this paper, by utilizing the dynamic nature of such gradual adjustment process, an induced spoofing detection method is proposed based on the S-curve-bias (SCB). Firstly, SCB in the inducing process is theoretically derived. Then, in order to detect the induced spoofing, a detection metric is defined. After that, a series of experiments using the Texas spoofing test battery (TEXBAT) are performed to demonstrate the effectiveness of the proposed algorithm. Full article
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Open AccessArticle Spoofing Detection and Mitigation in a Multi-correlator GPS Receiver Based on the Maximum Likelihood Principle
Sensors 2019, 19(1), 37; https://doi.org/10.3390/s19010037
Received: 27 October 2018 / Revised: 13 December 2018 / Accepted: 19 December 2018 / Published: 22 December 2018
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Abstract
As a structural interference, spoofing is difficult to detect by the target receiver while the advent of a repeater makes the implementation of spoofing much easier. Most existing anti-spoofing methods are merely capable of detecting the spoofing, i.e., they cannot effectively remove counterfeit [...] Read more.
As a structural interference, spoofing is difficult to detect by the target receiver while the advent of a repeater makes the implementation of spoofing much easier. Most existing anti-spoofing methods are merely capable of detecting the spoofing, i.e., they cannot effectively remove counterfeit signals. Therefore, based on the similarities between multipath and spoofing, the feasibility of applying multipath mitigation methods to anti-spoofing is first analyzed in this paper. We then propose a novel algorithm based on maximum likelihood (ML) estimation to resolve this problem. The tracking channels with multi-correlators are constructed and a set of corresponding steps of detecting and removing the counterfeit signals is designed to ensure that the receiver locks the authentic signals in the presence of spoofing. Finally, the spoofing is successfully executed with a software receiver and the saved intermediate frequency (IF) signals, on this basis, the effectiveness of the proposed algorithm is verified by experiments. Full article
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Open AccessArticle A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System
Sensors 2018, 18(11), 3809; https://doi.org/10.3390/s18113809
Received: 7 October 2018 / Revised: 30 October 2018 / Accepted: 1 November 2018 / Published: 6 November 2018
Cited by 2 | PDF Full-text (12496 KB) | HTML Full-text | XML Full-text
Abstract
Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and [...] Read more.
Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method. The impact of innovation perturbation produced by measurement outliers is found to account for positive feedback and numerical issues. Measurement noise covariance is updated based on a remodification algorithm according to measurement reliability specifications. An experimental field test was performed to demonstrate the robustness of the proposed state estimation method against dynamic model errors and measurement outliers. Full article
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