Passive interference localization within the GNSS environmental monitoring system (GEMS): TDOA aspects

Cetin, Ediz; Thompson, Ryan; Dempster, Andrew G.

doi:10.1007/s10291-014-0393-5

Cited by 22 publications

(10 citation statements)

References 20 publications

(17 reference statements)

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“…The TDOA could be estimated by the TDOAE model given by Equation . After the TDOA is estimated, the spoofer could be located at the intersection of N − 1 hyperbolas ( N is the number of the receivers) . It is noted that to locate a spoofer, the system should adopt at least three receivers with known positions .…”

Section: Directions For Future Studiesmentioning

confidence: 99%

Statistical analysis of spoofing detection based on TDOA

Zhang

Zhan

2018

IEEJ Transactions Elec Engng

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Recently, the vulnerability of a global navigation satellite system (GNSS) to spoofing has become more serious. This paper proposes a low-cost time difference of arrival estimation (TDOAE)-based spoofing detection system consisting of two individual receivers. The system could be easily deployed and implemented for anti-spoofing and further research purposes as it is softwaredefined and does not require additional hardware support. The TDOAE of a GNSS signal is mathematically formulated and is used for spoofing detection. As shown, in spoofed cases, the TDOAEs of spoofing signals are identical as spoofing signals are transmitted from a common spoofer. By contrast, the TDOAEs of authentic signals are various as they are from various directions. The hypothesis test is proposed based on such a difference in TDOAE. Simulation and real-data experiments validate the effectiveness of the spoofing detection technique, with 99.99% detection and <0.001% false alarm probabilities.

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Section: Directions For Future Studiesmentioning

confidence: 99%

Statistical analysis of spoofing detection based on TDOA

Zhang

Zhan

2018

IEEJ Transactions Elec Engng

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“…It mainly aims at the localization of targets on the ocean. Cetin et al proposed to combine AOA and TDOA technologies together . The centroid intersection method combined with AOA is used for narrow band interference localization.…”

Section: Introductionmentioning

confidence: 99%

“…Cetin et al proposed to combine AOA and TDOA technologies together. 12 The centroid intersection method combined with AOA is used for narrow band interference localization. Meanwhile, the Levenberg-Marquardt iteration method with TDOA is used for wide band interference.…”

Section: Introductionmentioning

confidence: 99%

“…Precise monitoring of receiver clock synchronization (required for TDOA estimation) and antenna array (required for AOA estimation) are the prerequisites for this algorithm, so the cost of each monitoring node is high. Note that the performance test scenarios in other works are open area where the interference transmission mainly belongs to line‐of‐sight (LoS) transmission. In urban environments, when signals transmit to monitoring nodes through non‐line‐of‐sight (NLoS) paths, the performance based on these technologies will significantly degrade because the angle and time estimated by monitoring nodes have large errors caused by NLoS signals.…”

Section: Introductionmentioning

confidence: 99%

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Urban area GNSS in‐car‐jammer localization based on pattern recognition

et al. 2019

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A GNSS in‐car‐jammer poses a great threat to the security of navigation satellite signals for civilian applications. Traditional interference localization methods such as received signal strength (RSS), signal arrival angle (AOA), and signal arrival time difference (TDOA) have poor performance in urban environments due to line‐of‐sight (LoS) path obstruction and reflection. In this paper, a new interference localization method, which works on monitoring networks and follows the pattern recognition principle is proposed. The algorithm locates the jammer by learning the carrier‐to‐noise density ratio features that are extracted from the data of all monitoring nodes of the network with the means of binary tree support vector machine (SVM) classification technology. Its performance is tested by two simulated interference scenarios: the urban canyon and the urban residential area. Results show that the algorithm provides better localization reliability and smaller position errors compared with traditional localization methods.

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“…So, a more active solution such as spoofer localization is required. Until now, some jammer localization methods have used time-difference-of-arrival (TDOA) and hybrid TDOA/angle-of-arrival (Lindström et al 2007, Bhatti et al 2012, Cetin et al 2014, Lim et al 2014. In these cases, array processing has been used for localizing the jamming signal source.…”

Section: Introductionmentioning

confidence: 99%

Ranging Performance for Spoofer Localization using Receiver Clock Offset

Lee¹,

Seo²,

Jee³

et al. 2016

Journal of Positioning, Navigation, and Timing

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In this paper, the performance of ranging measurement, which is generated using two receiver clock offsets in one receiver, was analyzed. A spoofer transmits a counterfeited spoofing signal which is similar to the GPS signal with hostile purposes, so the same tracking technique can be applied to the spoofing signal. The multi-correlator can generate two receiver clock offsets in one receiver. The difference between these two clock offsets consists of the path length from the spoofer to the receiver and the delay of spoofer system. Thus, in this paper, the ranging measurement was evaluated by the spoofer localization performance based on the time-of-arrival (TOA) technique. The results of simulation and real-world experiments show that the position and the system clock offset of the spoofer could be estimated successfully.

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Passive interference localization within the GNSS environmental monitoring system (GEMS): TDOA aspects

Cited by 22 publications

References 20 publications

Statistical analysis of spoofing detection based on TDOA

Statistical analysis of spoofing detection based on TDOA

Urban area GNSS in‐car‐jammer localization based on pattern recognition

Ranging Performance for Spoofer Localization using Receiver Clock Offset

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