• Journal of Information Processing Systems
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• 제18권1호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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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.

• 한국군사과학기술학회지
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• 제23권3호
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• pp.221-228
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• 2020

This paper presents the radar counter jamming algorithm and ground far-field test results for the pull-off deceptive jamming signals like RGPO(Range Gate Pull Off) and VGPO(Velocity Gate Pull Off). We designed the radar counter jamming algorithm according to the characteristics of the deceptive jamming signals. This algorithm is validated by simulation before ground far-field test. The existing X-band AESA radar demonstrator was used to test the proposed algorithm. The proposed algorithm was applied to the radar processor software. The deceptive jamming signals generated using the commercial jamming signal generator. We performed the repeated ground far-field test with the test scenario. Test results show that the proposed counter deceptive jamming algorithm works in the real radar system.

• 한국위성정보통신학회논문지
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• 제11권3호
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• pp.32-36
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• 2016

무선 통신 시스템에서 재밍 공격은 통신 성능을 심각하게 저하시킬 수 있는 치명적 위협이다. 특히 반응 재밍은 송신기와 수신기가 통신할 때만 재밍할 수 있기 때문에 반응 재밍을 통해 공격 효율을 극대화할 수 있다. 본 논문에서 반응 재밍의 공격 효과를 저감시키기 위해 multi-input multi-output (MIMO) 기반의 orthogonal frequency-division multiplexing (OFDM) 통신 기술의 특징을 활용하고, 이에 기반한 반복적 채널 추정 알고리즘을 제안하였다. 실험 결과를 통해 본 논문에서 제안한 알고리즘과 기존 항재밍 알고리즘을 비교하였으며, 반응 재밍 공격이 있는 MIMO-OFDM 통신 시스템에서 제안한 알고리즘의 우수성을 입증한다.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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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 Positioning, Navigation, and Timing
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• 제9권2호
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• pp.51-57
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• 2020

For the purpose of development of anti-jamming GPS receiver we have developed an anti-jamming algorithm and its Simulink implementation model. The algorithm used here is a form of Space-Time Adaptive Processing (STAP) filter which is well known as an effective way to remove wideband jamming signals. We have chosen Minimum Variance Distortionless Response (MVDR) block-adaptive beamforming algorithm for our development since it can provide relatively fast convergence speed to reach optimal weights, stable and high suppression capability on various types of jamming signals. We will show modeling results for this MVDR type adaptive beamformer and some simulation results. We also show the integrity of the demodulated satellite signals and the accuracy of resulting navigation solutions after anti-jamming operation.

• 전기학회논문지
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• 제60권11호
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• pp.2131-2138
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• 2011

GPS is vulnerable to jamming because of extremely low signal power. Many anti-jamming techniques are studied for complement this vulnerability. Anti-jamming techniques using array antenna are most effective technique and these techniques are required the DOA estimates. MUSIC algorithm and Root-MUSIC Algorithm are typical algorithms used in DOA estimation. Two algorithms have different characteristics, so the choice of an algorithm may depends on many factors such as the environment and the system requirements. The analysis and performance comparison of both algorithms is necessary to choose the best method to apply. This paper summarizes the theory of MUSIC and Root-MUSIC algorithms. And this paper extends both algorithm to estimate two-dimensional angles. The software simulator of both algorithms are implemented to evaluate the performance. Root-MUSIC algorithm has the computational advantage on ULA. MUSIC algorithm is applicable to any antenna array. MUSIC shows better estimation performance when number of array element is small while the computational load of MUSIC is much higher than Root-MUSIC.

• Journal of Positioning, Navigation, and Timing
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• 제8권1호
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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.

• 한국정보전자통신기술학회논문지
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• 제12권4호
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• pp.419-424
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• 2019

본 논문에서는 광대역 재밍 신호 환경에서 원하는 목표물을 추정하기 위한 알고리즘을 제안 한다. 재밍 신호를 억제하는 방법으로, 본 연구에서는 시공간적응 알고리즘과 QR분해를 사용하여 최적의 가중치를 획득한다. 시공간적응 알고리즘은 적응배열안테나시스템에서 탭 지연 신호에 복소 가중치를 곱하여 가중치를 생성하고, 역행렬로 인한 전력소모를 최소화하기 위해서 QR분해를 이용하여 최적의 가중치를 획득한다. 모의실험을 통하여, 본 연구에서 제안한 알고리즘과 기존 알고리즘의 성능을 비교 분석한다. [-40o,0o,+40o]의 목표물 추정에서 본 연구에서 제안 한 알고리즘이 3개의 목표물을 모두 추정하였지만 기존 알고리즘은 재밍 신호 때문에 [0o]에서만 추정하였다. 본 연구의 제안 알고리즘이 재밍 신호를 제거하고 원하는 목표물을 정확히 추정하여 성능이 향상되었음을 입증하였다.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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• pp.181-189
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• 2022

The public open signals from Global Navigation Satellite System (GNSS) including Global positioning system (GPS) are used widely by many peoples in the world except for the public regulated restriction signals which are encrypted. Nowadays there are growing concerns about GNSS signal spoofing which can deceive the GNSS receivers by abusing these open services. To counter these spoofing threats, many researches have been studied including array antenna techniques which can detect the direction of arrival by means of Multiple Signal Classification (MUSIC) algorithm. Originally the array antenna techniques were developed to countermeasure the jamming signal in electronic warfare by using the nulling or beamforming algorithm toward a certain direction. In this paper, we study the anti-spoofing techniques using array antenna to overcome the jamming and spoofing issues simultaneously. First, we will present the theoretical analysis results of spoofing signal response of Minimum Variance Distortionless Response (MVDR) algorithm in array antenna. Then the eigenvector algorithm of covariance matrix is suggested and verified to work with the existing anti-jamming method. The modeling and simulation are used to verify the effectiveness of the anti-spoofing algorithm. Also, the field test results show that the array antenna system with the proposed algorithms can perform the anti-spoofing function. This anti-spoofing method using array antenna is very effective in the view point of solving both the jamming and spoofing problems using the same array antenna hardware.