• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.468-472
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• 2000

This paper discusses the development of a acoustic vector channel simulator for the performance analysis of a acoustic digital communication system. The channel simulator consists of transmission module, acoustic channel model, receiver, beamformer, and adaptive equalizer. QPSK source signal is generated by the parameters specified by a user and transmitted. The transmitted signal generate multipath signals which have a different delay, amplitude, and dopper Sequency. The multipath signals with the acoustic noises is the received signal. We can analysis the communication system performance according to the antenna structure, beamforming algorithm, and equalization algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.83-89
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• 2000

Antenna arrays at base-stations can be used to transmit and receive information selectively in space by reducing the interference effects. In this paper, a new model of locally scattered signals in the vicinity of mobiles is proposed, and under this model the weights of the beamformer are obtained. Computer simulation results demonstrate that the proposed scheme shows an excellent performance and works well even in the urban environment where there exist many multipath propagations with wide angular spread.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.2
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• pp.187-195
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• 2012

In this paper, we propose the optimization of subarray configurations for linear array to minimize the side lobe level (SLL) in sum beam pattern based on the genetic algorithm. The operations of genetic algorithm are modified to be applied to subarray configurations. Using the proposed method, we construct subarray structure with 16 irregular subarray elements from 40 linear array elements to minimize the SLL in sum beam pattern in case of applying the adaptive beamforming(ABF) to suppress the jamming power, whose the SLL is 10 dB lower than that of regular subarray configuration.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.393-407
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• 2020

In order to reduce the threat by illegal unmanned aerial vehicles, a tracking system based on sound was implemented. There are three main points to the drone acoustic tracking method. First, it scans the space through variable beam formation to find a sound source and records the sound using a microphone array. Second, it classifies it into a hidden Markov model (HMM) to find out whether the sound source exists or not, and finally, the sound source is In the case of a drone, a sound source recorded and stored as a tracking reference signal based on an adaptive beam pattern is used. The simulation was performed in both the ideal condition without background noise and interference sound and the non-ideal condition with background noise and interference sound, and evaluated the tracking performance of illegal drones. The drone tracking system designed the criteria for determining the presence or absence of a drone according to the improvement of the search distance performance according to the microphone array performance and the degree of sound pattern matching, and reflected in the design of the speech reading circuit.

• The Journal of the Acoustical Society of Korea
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• v.11 no.2
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• pp.73-84
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• 1992

This paper studies noise subtraction methods and distance measures for speech recognition in a noisy environment, and investigates noise robustness of the distance measures applied to the problem of isolated word recognition in white Gaussian and colored noise (vehicle noise) environments. Noise subtraction methods which can be used as a pre-processor for the speech recognition system, such as the spectral subtraction method, autocorrelation subtraction method, adaptive noise cancellation and acoustic beamforming are studied, and distance measures such and Log Likelihood Ratio ($d_{LLR}$), cepstral distance measure ($d_{CEP}$), weighted cepstral distance measure ($d_{WCEP}$), spectral slope distance measure ($d_{RPS}$) and cepstral projection distance measure ($d_{CP},\;d_{BCP},\;d_{WCP},\;d_{BWCP}$) are also investigated. Testing of the distance measures for speaker-dependent isolated word recognition in a noisy environment indicate that $d_{RPS}\;and\;d_{WCEP}$ which weigh higher order cepstral coefficients more heavily give considerable performance improvement over $d_{CEP}and\;d_{LLR}$. In addition, when no pre-emphasis is performed, the recognizer can maintain higher performance under high noise conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.579-585
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• 2002

The investigation into the effect of various feedback errors on system performance can help the robust feedback channel design and transmission of exact feedback channel information as well. In this paper, we address the algorithm that determines space combining weight vector maximizing received signal power at mobile on frequency flat fading channel and investigate the performance degradation by feedback channel delay in the FDD/CDMA systems employing transmit beamforming. We observe the effect of feedback channel delay corresponding to the number of transmit antennas and the temporal/spatial correlation of channel. The results show that performance is more sensitive to feedback delay with the larger number of antennas when fadings at transmit antennas are not spatially correlated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.413-420
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• 2011

This paper proposes a new adaptive algorithm to cancel the acoustic feedback and noise signals in the binaural hearing aids. The convergence performances of the proposed algorithm are improved by updating coefficients of the feedback canceller after the speech signal is cancelled from the residual signal with dual microphones. The feedback canceller firstly cancels the feedback signal from the microphone signal, and then the noise canceller reduces the noise by the beamforming method. To assure that binaural hearing aids converge stably, the left-sided hearing aid only is converged firstly, next the right-sided hearing aid only is converged. To verify performances of the proposed algorithm, simulations were carried out for a speech. As the results of simulations, it was proved that we can advance 14.43dB SFR(Signal to Feedback Ratio) on the average for the feedback canceller, 10.19dB SNR(Signal to Noise Ratio) improvement on the average for the noise canceller, in case that this algorithm is used.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.713-720
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• 2018

The Signal Intelligence (SIGINT) system based on Angle-of-Arrival(AOA) estimation, interference suppression, and transmission beamforming techniques is a cutting edge technology for efficiently collecting various signal information. In this paper, we present the efficient structure of a satellite system consisted of an AOA estimator, an adaptive beamformer, a signal processing and D/B unit, and a transmission beamformer, for collecting signal information. For accurately estimating AOAs of various signals, efficiently suppressing interference or jamming signals, and efficiently transmitting the collected information or data, we employ Multiple Signal Classification (MUSIC), Minimum Variance Distortionless Response (MVDR), and Minimum Mean Square Error (MMSE) algorithms, respectively. Also, we evaluate and analysis the performance of the presented satellite system through the computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.624-633
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• 2018

While the multimedia lecture system has been getting smart using immerging technology, the microphone still relies on the classical approach such as holding in hand or attaching on the body. In this paper, we propose a ceiling mounted array microphone system that allows a wide reception coverage and instructors to move freely without attaching microphone. The proposed system adopts cell and handover of mobile communication instead of a complicated beamforming method and implements a wide range microphone over several cells with low cost. Since the characteristics of unvoiced speech is similar to Pseudo Noise it is shown that soft handover are possible with 3 microphones connected to delay-sum multipath receiver. The proposed system is tested in $6.3{\times}1.5m$ area. For real-time processing the correlation range can be reduced by 82% or more, and the output latency delay can be improved by using the delay adaptive filter.