GNSS Threat Monitoring and Reporting: Past, Present, and a Proposed Future

Thombre, Sarang; Bhuiyan, Mohammad Zahidul H.; Eliardsson, Patrik; Gabrielsson, Bjorn; Pattinson, Michael; Dumville, Mark; Fryganiotis, Dimitrios; Hill, Steve; Manikundalam, Venkatesh; Pölöskey, Martin; Lee, Sang-Uk; Ruotsalainen, Laura; Söderholm, Stefan; Kuusniemi, Heidi

doi:10.1017/s0373463317000911

Cited by 45 publications

(34 citation statements)

References 3 publications

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“…At the beginning of the 21st century, jamming was considered the most common threat. The accuracy and availability of the receiver's position solution during the interference were analyzed, for example, in the STRIKE3 project [25]. This investigation shows that as the interference power increases, the receiver performance continues to degrade and finally loses the position fix.…”

Section: Navigation Threatsmentioning

confidence: 99%

The Ocean-Going Autonomous Ship—Challenges and Threats

Felski

Zwolak

2020

JMSE

126

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Unmanned vehicles have become a part of everyday life, not only in the air, but also at sea. In the case of sea, until now this usually meant small platforms operating near shores, usually for surveying or research purposes. However, experiments with larger cargo vessels, designed to operate on the high seas are already being carried out. In this context, there are questions about the threats that this solution may pose for other sea users, as well as the safety of the unmanned vehicle itself and the cargo or equipment on board. The problems can be considered in the context of system reliability as well as the resilience to interference or other intentional actions directed against these objects—for example, of a criminal nature. The paper describes the dangers that arise from the specificity of systems that can be used to solve navigational problems, as well as the analysis of the first experiences of the authors arising from the transit of an unmanned surface vessel (USV) from the United Kingdom to Belgium and back, crossing the busiest world shipping route—the English Channel.

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Section: Navigation Threatsmentioning

confidence: 99%

The Ocean-Going Autonomous Ship—Challenges and Threats

Felski

Zwolak

2020

JMSE

126

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“…According to their tests, the jammer's output features a period of 10 µs, while according to our test it, the device raises noise power up to 50 dB in a frequency band of 1570 MHz ± 20 MHz. Following the STRIKE3 (Standardisation of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation) attempt of standardised threat reporting of jamming events [15], the effect of this particular jammer should be described as an interference event Type B, exerting a 10 dB decrease of C/N 0 lasting for more than 5 s. Exchange, Experimentation and Exploitation) attempt of standardised threat reporting of jamming events [15], the effect of this particular jammer should be described as an interference event Type B, exerting a 10 dB decrease of C/N0 lasting for more than 5 s.…”

Section: Gnss Jammer Characterisationmentioning

confidence: 99%

Evaluating the Vulnerability of Several Geodetic GNSS Receivers under Chirp Signal L1/E1 Jamming

Bažec

Dimc

Pavlovčič-Prešeren

2020

Sensors

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Understanding the factors that might intentionally influence the reception of global navigation satellite system (GNSS) signals can be a challenging topic today. The focus of this research is to evaluate the vulnerability of geodetic GNSS receivers under the use of a low-cost L1/E1 frequency jammer. A suitable area for testing was established in Slovenia. Nine receivers from different manufacturers were under consideration in this study. While positioning, intentional 3-minute jammings were performed by a jammer that was located statically at different distances from receivers. Furthermore, kinematic disturbances were performed using a jammer placed in a vehicle that passed the testing area at various speeds. An analysis of different scenarios indicated that despite the use of an L1/E1 jammer, the GLONASS (Russian: Globalnaya Navigatsionnaya Sputnikovaya Sistema) and Galileo signals were also affected, either due to the increased carrier-to-noise-ratio (C/N0) or, in the worst cases, by a loss-of-signal. A jammer could substantially affect the position, either with a lack of any practical solution or even with a wrong position. Maximal errors in the carrier-phase positions, which should be considered a concern for geodesy, differed by a few metres from the exact solution. The factor that completely disabled the signal reception was the proximity of a jammer, regardless of its static or kinematic mode.

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“…The anomaly detectors proposed in literature can be mainly brought down to two major classes: unsupervised and semisupervised anomay detection. 3…”

Section: Related Workmentioning

confidence: 99%

Crowdsourced Wireless Spectrum Anomaly Detection

Rajendran

Lenders²,

Meert

et al. 2020

IEEE Trans. Cogn. Commun. Netw.

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Automated wireless spectrum monitoring across frequency, time and space will be essential for many future applications. Manual and fine-grained spectrum analysis is becoming impossible because of the large number of measurement locations and complexity of the spectrum use landscape. Detecting unexpected behaviors in the wireless spectrum from the collected data is a crucial part of this automated monitoring, and the control of detected anomalies is a key functionality to enable interaction between the automated system and the end user. In this paper we look into the wireless spectrum anomaly detection problem for crowdsourced sensors. We first analyze in detail the nature of these anomalies and design effective algorithms to bring the higher dimensional input data to a common feature space across sensors. Anomalies can then be detected as outliers in this feature space. In addition, we investigate the importance of user feedback in the anomaly detection process to improve the performance of unsupervised anomaly detection. Furthermore, schemes for generalizing user feedback across sensors are also developed to close the anomaly detection loop.

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GNSS Threat Monitoring and Reporting: Past, Present, and a Proposed Future

Cited by 45 publications

References 3 publications

The Ocean-Going Autonomous Ship—Challenges and Threats

The Ocean-Going Autonomous Ship—Challenges and Threats

Evaluating the Vulnerability of Several Geodetic GNSS Receivers under Chirp Signal L1/E1 Jamming

Crowdsourced Wireless Spectrum Anomaly Detection

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