Coding Aspects of Secure GNSS Receivers

Curran, James T.; Navarro, Mònica; Anghileri, Marco; Closas, Pau; Pfletschinger, Stephan

doi:10.1109/jproc.2016.2530317

Cited by 16 publications

(16 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is proposed that this information might be exploited by an adversary to trigger short pulses of interference which are tightly aligned with certain portions of the navigation message of each satellite. Previous work has demonstrated that, a low duty-cycle pulsed interference, that is appropriately synchronized with the navigation message, can cause disruption to the receiver data recovery process, equivalent to that of an always-on interference [1]. This process requires that the pulse pattern be designed to specifically target weaknesses in the navigation message coding scheme, and it has been shown that for the case of convolutional encoding and block interleaving that a malicious adversary might inflict a denial-of-service (DOS) upon a naïve receiver, using an average interference power 10 to 20 dB lower than the continuous interference case.…”

Section: Problem Definitionmentioning

confidence: 99%

“…The most relevant specifications for these two devices are in Tab. 1 Designing and building a sophisticated jammer would be a controversial research activity and would pass the message that synchronised jamming needs specialist expertise and skilled personnel, when instead it is relatively simple. Using a general purpose transceiver reading samples Such IF file can be played back in a loop for as long as the reference clock of the transceiver maintains good synchronisation with the navigation data bits to be jammed.…”

Section: Anatomy Of a Systematic Jammermentioning

confidence: 99%

See 1 more Smart Citation

On the Threat of Systematic Jamming of GNSS

Curran¹,

Bavaro²,

Closas³

et al. 2016

Proceedings of the 29th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 201

Self Cite

View full text Add to dashboard Cite

He has worked as a research engineer with the PLAN Group in the University of Calgary, and at the JRC in, Italy. He is currently a radionavigation engineer with Serco for ESA in Noordwijk, the Netherlands. His research interests include signal processing, information theory, cryptography and software defined radio for GNSS. Michele Bavaro received his master degree in Computer Science in 2003 from the University of Pisa. Shortly afterwards he started his work on Software Defined Radio technologies applied to navigation. First in Italy, then in The Netherlands and in the UK he worked on several projects being directly involved with the design, manufacture, integration, and test of radio navigation equipment and supporting customers in the development of their applications. Today he is appointed as Technical Project

show abstract

Section: Problem Definitionmentioning

confidence: 99%

Section: Anatomy Of a Systematic Jammermentioning

confidence: 99%

On the Threat of Systematic Jamming of GNSS

Curran¹,

Bavaro²,

Closas³

et al. 2016

Proceedings of the 29th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 201

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, a key part of GNSS receivers is the data demodulation stage, which allows recovering essential information. The latter has been long disregarded, with only a few articles [32][33][34][35] in the state-of-the-art, but may be a critical point under interference scenarios, being the principal object of this article.…”

Section: Introductionmentioning

confidence: 99%

“…The latter causes the symbol instantaneous variance σ 2 n to be altered. In [32], to compute the LLR under scenarios with interference, the variance was proposed to be symbol-wise estimated by the maximum likelihood (ML) principle. However, in general, this criterion is known to be computationally demanding and not accurate when a low number of samples per symbol are available.…”

Section: Introductionmentioning

confidence: 99%

Low Complexity Robust Data Demodulation for GNSS

Ortega¹,

Poulliat

Boucheret

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

In this article, we provide closed-form approximations of log-likelihood ratio (LLR) values for direct sequence spread spectrum (DS-SS) systems over three particular scenarios, which are commonly found in the Global Navigation Satellite System (GNSS) environment. Those scenarios are the open sky with smooth variation of the signal-to-noise ratio (SNR), the additive Gaussian interference, and pulsed jamming. In most of the current communications systems, block-wise estimators are considered. However, for some applications such as GNSSs, symbol-wise estimators are available due to the low data rate. Usually, the noise variance is considered either perfectly known or available through symbol-wise estimators, leading to possible mismatched demodulation, which could induce errors in the decoding process. In this contribution, we first derive two closed-form expressions for LLRs in additive white Gaussian and Laplacian noise channels, under noise uncertainty, based on conjugate priors. Then, assuming those cases where the statistical knowledge about the estimation error is characterized by a noise variance following an inverse log-normal distribution, we derive the corresponding closed-form LLR approximations. The relevance of the proposed expressions is investigated in the context of the GPS L1C signal where the clock and ephemeris data (CED) are encoded with low-density parity-check (LDPC) codes. Then, the CED is iteratively decoded based on the belief propagation (BP) algorithm. Simulation results show significant frame error rate (FER) improvement compared to classical approaches not accounting for such uncertainty.

show abstract

“…GNSS is recognized to be the de facto system in outdoor environments when it is available. Under the assumption that its reception is not obstructed or jammed [2][3][4], there is no doubt that GNSS is the main enabler for location-based services (LBS). One of such situations is indoor positioning and tracking, where satellite signals are hardly useful (unless extremely large integration times are considered).…”

Section: Introductionmentioning

confidence: 99%

NLOS mitigation in indoor localization by marginalized Monte Carlo Gaussian smoothing

Vilà‐Valls

Closas

2017

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

One of the main challenges in indoor time-of-arrival (TOA)-based wireless localization systems is to mitigate non-line-of-sight (NLOS) propagation conditions, which degrade the overall positioning performance. The positive skewed non-Gaussian nature of TOA observations under LOS/NLOS conditions can be modeled as a heavy-tailed skew t-distributed measurement noise. The main goal of this article is to provide a robust Bayesian inference framework to deal with target localization under NLOS conditions. A key point is to take advantage of the conditionally Gaussian formulation of the skew t-distribution, thus being able to use computationally light Gaussian filtering and smoothing methods as the core of the new approach. The unknown non-Gaussian noise latent variables are marginalized using Monte Carlo sampling. Numerical results are provided to show the performance improvement of the proposed approach.

show abstract

Coding Aspects of Secure GNSS Receivers

Cited by 16 publications

References 28 publications

On the Threat of Systematic Jamming of GNSS

On the Threat of Systematic Jamming of GNSS

Low Complexity Robust Data Demodulation for GNSS

NLOS mitigation in indoor localization by marginalized Monte Carlo Gaussian smoothing

Contact Info

Product

Resources

About