• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.1-5
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• 2016

As a dependency on Global Navigation Satellite System (GNSS) becomes increase in various applications, its reliability has been very important. However, in South Korea, Global Positioning System (GPS) jamming incident happened four times since 2010. GNSS signal is so weak that it is highly susceptible to all types of the jamming. GNSS jamming can cause serious damage in the safety-critical applications based on the GNSS. In this paper, we present the GNSS jamming signal propagation prediction simulator based on ITU-R P.1546 model. This simulator is developed for preventing or reducing the damage from the GNSS jamming attack by predicting the jamming propagation strength based on the geographical information in Korean peninsula.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.116-125
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• 2020

Incalculable damage will be incurred if the national infrastructure that provides services using GNSS signals is affected by jamming signals. To prevent this, a nationwide GNSS jamming monitoring network is necessary to detect the occurrence of a jamming signal, determine the type, and properly localize the jammer position. In this paper, 2-D images for live GNSS signals were generated to verify the environment of the jamming signals through the presence and type of GNSS jamming signals at K-City, which are the test beds for self-driving vehicles, and Incheon International Airport. The analysis was also conducted to detect the occurrence of the jamming signals, determine the type, and measure the jamming signal strength. As a result, a CWI type of jamming signal was detected in L2 band at K-City and in L5 band at Incheon International Airport.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.133-139
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• 2010

GNSS receiver which uses the weak satellite signal is very vulnerable to the intentional jamming or non-intentional electromagnetic interference. It is a very simple method among the use method of GNSS receiver to vary tracking loop bandwidth of satellite signal appropriately as the jamming signal level. In this paper, this anti-jamming performance is experimented and analyzed in the laboratory and the anechoic chamber by the GNSS simulator to generate the satellite signal and the jamming signal generator to generate the jamming signal.

• Journal of Navigation and Port Research
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• v.34 no.2
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• pp.97-103
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• 2010

It has been recognized that the risk from the vulnerability of GPS can lead to the extreme damage in the infrastructure of the civil and military in recent years. As an example, the intentional interference to GPS signal, named GPS jamming, was really performed to misguide GPS guided weapons during Iraq war in 2003, and the fact has also followed by the serious issues on GPS in civilian community. In the modernized military society, the navigation warfare(NAVWAR) based on the GPS jamming has been emerged and introduced as a military operation. The intentional interference to the future global navigation satellite system(GNSS) involving GPS must be also an important issue to civilian users in near future. This study is focused on the fundamental research prior to the research on "Potential principle of NAVWAR" under NAVWAR of the future warfare. In this paper, we would study on the investigation of NAVWAR based on electronic warfare(EW) and analyze characteristics of the jamming against GNSS's receivers. Then the general mechanism on GNSS jamming is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.977-983
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• 2014

A repeat-back jamming signal is an intentionally re-broadcasted GNSS (Global Navigation Satellite System) interference. In this paper, a novel repeat-back jamming detection scheme is proposed. The proposed scheme uses a combined pseudo random noise signal (C-PRN) and is available for a generic GNSS receiver with a single antenna. The C-PRN signal is made by combining several received pseudo random noise signals that had been transmitted from the visible GNSS satellites. Through a Monte-Carlo simulation, the detection probability of a repeat-back jamming signal detected with the proposed scheme is presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.74-85
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• 2021

Global Navigation Satellite System (GNSS) receivers are intrinsically vulnerable to radio frequency jamming signals due to the fundamental property of radio navigation systems. A GNSS jamming monitoring system that is capable of jamming detection, classification and localization is essential for infrastructure for autonomous driving systems. For these 3 functionalities, a GNSS jamming monitoring network consisting of a multiple of low-cost GNSS receivers distributed in a certain area is needed, and the precise time synchronizaion between multiple independent GNSS receivers in the network is an essential element. This paper presents a precise time synchronization method based on the direct use of Time Difference of Arrival (TDOA) technique in signal domain. A block interpolation method is additionally incorporated into the method in order to maintain the precision of time synchronization even with the relatively low sampling rate of the received signals for computational efficiency. The feasibility of the proposed approach is verified in the numerical simualtions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.79-94
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• 2021

A GNSS receiver installed in autonomous vehicles is the most essential device for its navigation. However, if an intentional jamming signal is generated, there is a risk of exposure to an accident risk due to deterioration of the GNSS sensor's performance. Research is required to prevent this, and accordingly, a jamming generating device must be provided. However, according to the provisions of the law related to jamming, this is illegal. In this paper, we implement an in-vehicle jamming device that complies with the provisions of the law and does not affect the surrounding GNSS sensors. Driving simulation is used to evaluate the performance of the GNSS algorithm, and the malfunction of autonomous vehicles occurring in the interference environment and data errors output from the GNSS sensor are analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1216-1227
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• 2013

GNSS(Global Navigation Satellite System) is now being widely used in both civilian and military applications where accurate positioning and timing information are required and it is considered as a representative convergence technique in IT-Military application techniques. However, GNSS has low sensitivity level of GNSS receivers and is vulnerable to jamming signal, since the signals come from the satellite located at approximately 20,000 Km above the earth. The studies for the anti-jamming techniques in military applications have been passively performed in the domestic, because the information related GNSS are dependent on the countries that have GNSS. In this paper, we show the effect of jammer ERP by analyzing the link budget of GPS J/S power as a function of distance between jammer and receiver. Also, we categorize the anti-jamming techniques based on the functional block diagram of GNSS receiver structure and analyze the recent anti-jamming GNSS products and their technologies developed in domestic and foreign countries.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.19-29
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• 2019

This paper analyzes the design factors for GNSS anti-jamming receiver system in which the adaptive beamforming algorithm is applied in GNSS receiver system. The design analysis factors used in this paper are divided into three: antenna, beamforming algorithm, and operation environment. This paper analyzes the above three factors and presents numerical simulation results on antenna and beamforming algorithm.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.163-172
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• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.