Jamming Meets Antijamming: A Survey of GPS Communication Networks

Yang, Yifan

doi:10.1155/2022/9438027

Cited by 6 publications

(4 citation statements)

References 35 publications

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“…The existing GNSS jamming methods are mainly classified into deceptive and suppressive jamming [5]. Suppressive jamming has the advantage of easy implementation, but most modern satellite navigation systems are equipped with a series of anti-jamming measures, including increasing signal transmission power, new code structures, and space-time filtering techniques [6][7][8], which significantly reduce the effect of suppressive jamming, and suppressive jamming is easily detected causing jamming failure.…”

Section: Introductionmentioning

confidence: 99%

Smart forwarding deceptive jamming distribution optimal algorithm

Tang,

Ding,

et al. 2024

IET Radar Sonar & Navi

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With the frequent occurrence of drone black flying in large stadiums and airports, the requirement of precise electromagnetic interference to achieve unmanned aerial vehicle (UAV) displacement and forced landing in these protected area became urgent. Since traditional suppression jamming will affect normal communication, and forwarding deceptive jamming has coverage hole, a smart forwarding deceptive jamming distribution optimal algorithm (SFDJDO) is proposed. It gives a mapping error scale factor and the optimal distribution of multistation forwarding equivalent mapping to solve the problem of distortion on the mapping scale caused by different distribution methods and reduces the influence of the mapping errors and the differences between the virtual and real point neighborhoods of the jamming source. A comparison of the proposed SFDJDO method to the existing jamming source distribution optimisation method is conducted in the aspect of area mapping and trajectory mapping. The findings reveal that when the GNSS receiver clock bias is within the capture range, SFDJDO demonstrates significant enhancements in mapping precision and jamming success rates.

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Section: Introductionmentioning

confidence: 99%

Smart forwarding deceptive jamming distribution optimal algorithm

Tang,

Ding,

et al. 2024

IET Radar Sonar & Navi

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“…Interdependent networks have become a powerful paradigm for characterising complex systems where the components may depend on each other. A typical scenario involves cyber-physical systems (CPS), where different functional networks, such as communication networks and power grids, interact with each other, and complex networks provide a general framework for modeling and analyzing these systems [1][2][3]. Although network interactions enable the system to operate more efficiently, they also bring many risks.…”

Section: Introductionmentioning

confidence: 99%

“…Since the introduction of the framework proposed by Buldyrev et al in 2010 [4], which analyzes the robustness of interdependent networks based on percolation theory, numerous studies have been conducted within this framework. However, most studies on the robustness of interdependent networks have focused on the one-to-one interdependence between the individual nodes [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. In the real world, some nodes always cooperate to form groups or cliques to enhance the system's robustness against risks.…”

Section: Introductionmentioning

confidence: 99%

Percolation in interdependent networks with groups and heterogeneous weak interdependency strength under targeted attack

Zhang,

Liu,

Liu

et al. 2024

Phys. Scr.

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Pairwise dependencies in interdependent networks exist not only between ordinary nodes but also between groups of nodes, where nodes cooperate and form groups to increase their robustness to risks and each group can be considered a ``supernode''. The interdependencies between supernodes are universal but not always complete and homogeneous. \textcolor{red}{In this paper, we study the robustness of interdependent networks with groups and heterogeneous weak interdependency strength under targeted attack, where the interdependency strength could vary between different supernodes.} We identify several types of percolation transitions, namely discontinuous, continuous, and hybrid, which are determined by the structure of the supernodes, the strengths of the interdependencies, and their distributions. We first apply this mathematical framework to the Erdös-Rényi and Scale-free interdependent networks with groups and homogeneous weak interdependency strength to calculate analytically and numerically the values of the phase transition thresholds and the critical interdependency strengths that distinguish different types of transitions. We then present examples of three distributions with different heterogeneous interdependency strengths. Our theoretical and numerical predictions are in close agreement, demonstrating that weaker interdependence strengths and higher levels of interdependence heterogeneity can enhance the robustness of interdependent networks under targeted attack.

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“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

mentioning

confidence: 99%

Retracted: Jamming Meets Antijamming: A Survey of GPS Communication Networks

and Communication Networks

2024

Security and Communication Networks

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Jamming Meets Antijamming: A Survey of GPS Communication Networks

Cited by 6 publications

References 35 publications

Smart forwarding deceptive jamming distribution optimal algorithm

Smart forwarding deceptive jamming distribution optimal algorithm

Percolation in interdependent networks with groups and heterogeneous weak interdependency strength under targeted attack

Retracted: Jamming Meets Antijamming: A Survey of GPS Communication Networks

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