• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2883-2902
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• 2023

Since the existing anti-jamming methods, including intelligent methods, have difficulty against high-speed reactive jamming, we studied a new methodology for jamming utilization instead of avoiding jamming. Different from the existing jamming utilization techniques that harvest energy from the jamming signal as a power supply, our proposed method can take the jamming signal as a favorable factor for frequency detection. Specifically, we design an intelligent differential frequency hopping communication framework (IDFH), which contains two stages of training and communication. We first adopt supervised learning to get the jamming rule during the training stage when the synchronizing sequence is sent. And then, we utilize the jamming rule to improve the frequency detection during the communication stage when the real payload is sent. Simulation results show that the proposed method successfully combated high-speed reactive jamming with different parameters. And the communication performance increases as the power of the jamming signal increase, hence the jamming signal can help users communicate in a low signal-to-noise ratio (SNR) environment.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.89-96
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• 2022

A novel multistage pulse jamming suppression algorithm was proposed to solve the anti-pulse jamming problem encountered in navigation receivers. Based on the characteristics of the short duration of pulse jamming and distribution characteristics of satellite signals, the pulse jamming detection threshold was derived. From the experiments, it was found that the randomness of pulse jamming affects jamming suppression. On this basis, the principle of the multistage anti-pulse jamming algorithm was established. The effectiveness of the anti-jamming algorithm was verified through experiments. The characteristics of the algorithm include simple determination of jamming detection threshold, easy programming, and complete suppression of pulse jamming.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.229-236
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• 2023

As the importance and dependency of the positioning, navigation, and timing (PNT) information provided by the radio navigation satellite service (RNSS) increases, the vulnerability of RNSS to jamming can lead to significant risks. The signal design under the consideration of anti-jamming performance helps to provide service which is robust to jamming environment. Therefore, it is necessary to evaluate the jamming robustness performance during the design of new signals. In this paper, we introduce figures-of-merit (FoMs) that can be used for an anti-jamming performance analysis of designed signals of interest. We then calculate the FoMs, such as the quality factor (Q factor), tolerable jamming-to-signal ratio (tolerable J/S), and range to jammer (d) for legacy RNSS signals and analyze the results. Finally, based on the results of the analysis, we derive waveform design conditions to obtain good anti-jamming performance. As a result, this paper shows that the waveforms with wide bandwidth leading to good spectral efficiency provide strong anti-jamming performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.115-123
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• 2018

In this paper, we consider the applicability of time-hopping(TH) systems for anti-jamming(AJ) communication. We first briefly summarize fundamentals of TH systems and several common jamming scenarios that have been considered in the literature. We then analyze the AJ performance of TH systems under those common jamming environments. From our simulation results, we reveal that among narrow band, partial band, broadband, and sweep jamming, partial band and sweep jamming are the best ones from jammer perspective. For the partial band jamming case, we show that the most effective bandwidth ratio and location are 50 % and 2.5-3.5 Ghz, respectively. For the sweep jamming case, we illustrate that the AJ performance of the TH system is enhanced when the sweep duration approaches to the bit duration. In addition, we pointed out that the most efficient jamming bandwidth ratio is 1/2. Finally, our results show that the TH-BPSK system greatly outperforms the TH-PPM counterpart.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.113-124
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• 2022

In wartime conditions, the communication system of military aircraft is exposed to jamming, and it is necessary to mount communication equipment with high anti-jamming performance in order to perform air operations smoothly even in an environment where jamming attempts are made. In this paper, we check in detail the jamming and anti-jamming technology that can be applied to wireless communication, and the data disclosed on the difference in specifications of the next-generation anti-jamming radio with frequency hopping method and the improvement of anti-jamming performance according to these changes. It was briefly analyzed within the scope. In addition, the points to be considered when designing a new domestic aircraft and the possibility of installing the next-generation anti-jamming communication equipment on the currently operating aircraft were confirmed, and the tactical usefulness of improving the anti-jamming capability of the next-generation anti-jamming communication equipment was confirmed.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.55-63
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• 2015

Recently, terroristic threats using a radio controlled improvised explosive device (RCIED) that is remotely controlled and exploded have been increased around the world. In order to prevent the explosion of an RCIED, jamming techniques that interrupt an RCIED receiver can be used, so that the receiver can not demodulate the trigger code. Conventional jamming technique is a type of active barrage jamming that always emits the noise jamming signal for all the frequency band. However, it needs large power consumption and thus is limited in operation time for a vehicle. In order to overcome the shortage of the active barrage jamming, reactive jamming technique has drawn attention. In reactive jamming, all the frequency band is firstly scanned, and then if any trigger signal exists, one emits the jamming signal to the corresponding frequency band. Therefore, the reactive jamming is superior to the active barrage jamming in terms of power efficiency. However, a reactive jammer emits a jamming signal only after the trigger signal is intercepted, which means that the jamming signal may be late for interrupting an RCIED receiver. In this sense, it is needed to evaluate a delay in an RCIED receiver. To achieve this, we analyze the reaction time and present the simulation result for jamming performance of reactive jamming against an RCIED using mobile devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3333-3350
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• 2019

The smart jammer launches jamming attacks which degrade the transmission reliability. In this paper, smart jamming attacks based on the communication probability over different channels is considered, and an anti-jamming Q learning algorithm (AQLA) is developed to obtain anti-jamming knowledge for the local region. To accelerate the learning process across multiple regions, a multi-regional intelligent anti-jamming learning algorithm (MIALA) which utilizes transferred knowledge from neighboring regions is proposed. The MIALA algorithm is evaluated through simulations, and the results show that the it is capable of learning the jamming rules and effectively speed up the learning rate of the whole communication region when the jamming rules are similar in the neighboring regions.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.32-36
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• 2016

In wireless communication systems, jamming attack is a critical threat. Especially, reactive jamming can jam when the sender and receiver are communicating, which can maximize the attack efficiency of jamming. In this paper, we use the property of multi-input multi-output (MIMO) technology to achieve jamming resilient orthogonal frequency-division multiplexing (OFDM) communications. In particular, we use MIMO interference cancellation to remove the jamming signals strategically. We first investigate the reactive jamming attack model and their impacts on the MIMO-OFDM systems. We then present an iterative channel estimation algorithm that exploits MIMO interference cancellation. Our simulations show various anti-jamming methods and demonstrate the efficiency of our proposed algorithm under the reactive jamming attack.