• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.801-802
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• 2012

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.139-142
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• 1999

본 연구는 폐쇄된 임의의 공간상에서 2개의 마이크로폰 어레이를 이용 수신된 2개 신호의 도착 시간차를 계산하여 응원의 방향 각을 추정하는 새로운 알고리듬을 제안한다. 제안된 MSCPSP 알고리듬은 기존의 CPSP 알고리듬을 개선한것으로, 마이크로폰에 수신된 2개의 입력신호에 대해 서브밴드 필터 뱅크를 이용하여 대역 분할하고 각 서브밴드 대역에서 구해지는 신호 대 잡음비(SNH)를 대역별 CPSP 결과에 가중치로 제공한다. 이러한 대역 분할 가중방식은 잡음의 영향을 각 대역으로 한정 분산시켜 보다 정확한 지연 시간 추정을 가능하게 한다. 제안된 알고리듬의 성능을 입증하기 위해 기존의 CPSP와 MSCPSP 알고리듬의 컴퓨터 모의 실험을 수행하였으며, 실험 결과 제안된 MSCPSP의 우수함을 볼 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.423-430
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• 2005

In this paper. a microphone array beamforming algorithm that reduces the signal distortion caused by reverberation and near-field effect in car environment is proposed. When reverberation or near-field effect is present, an optimum beamformer should be constructed with a steering vector consisting of transfer functions between source and microphones, but it is generally difficult to estimate transfer functions on-line without knowledge of the source signal. Instead, a sub-optimal beamforming algorithm that reduces signal distortion is proposed. It is constructed with steering vectors consisting of relative transfer functions between reference sensor and other sensors. In order to evaluate the performance of the proposed algorithm. we had recorded noisy speech database in a car, and performed speech recognition experiments with HMM Toolkit (HTK) released by Cambridge University. The recognition rate of the proposed algorithm was 15 percents higher than that of the conventional far-field beamformers in best case.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.975-985
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• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.72-77
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• 2024

Recently, the necessity for sound source localization has grown significantly across various industrial sectors. Among the sound source localization methods, sound intensimetry has the advantage of having high accuracy even with a small microphone array. However, the increase in localization error at high Helmholtz numbers have been pointed out as a limitation of this method. The study proposes a method to compensate for the bias error of the measured sound intensity vector according to the Helmholtz numbers by applying deep learning. The method makes it possible to estimate the accurate direction of arrival of the source by applying a dense layer-based deep learning model that derives compensated sound intensity vectors when inputting the sound intensity vectors measured by a tetrahedral microphone array for the Helmholtz numbers. The model is verified based on simulation data for all sound source directions with 0.1 < kd < 3.0. One can find that the deep learning-based approach expands the measurement frequency range when implementing the sound intensimetry-based sound source localization method, also one can make it applicable to various microphone array sizes.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.271-279
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• 2016

Pantograph aerodynamic noise is a major cause of noise that occurs when a train is traveling at high speeds. In this study, in order to analyze the contribution of pantograph aerodynamic noise, real train tests using HEMU-430X were carried out. In order to analyze the frequency characteristic of the noise of the pantograph in an actual vehicle, a sound field visualization has been carried out using a 144-channel microphone array at train speeds of 350 and 400km/h. As a result, it was confirmed that the low frequency noise in the 250~400Hz bandwidth provides the main contribution to the pantograph noise. And, in order to estimate the noise contribution of the pantograph, the noise level difference between cases in which the pantograph is ascending and those in which it is descending were compared in single microphone experiments. The frequency analysis in the single microphone tests showed that the bands of 315~400Hz and 1000~1250Hz are the main frequency characteristics of pantograph noise. These results show quite good agreement with those of previous studies and with results of sound field visualization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1573-1580
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• 2004

In this paper, an adaptation mode controller for adaptive microphone array system is proposed for high-quality speech acquisition in real environments. To ensure proper adaptation of the adaptive array algorithm, the proposed adaptation mode controller uses not only temporal information, but also spatial information. The proposed adaptation mode controller is constructed with two processing stages: an initialization stage and a running stage. In the initialization stage, a sound source localization technique is adopted, and a signal correlation characteristic is used in the running stage. For the adaptive may algorithm, a generalized sidelobe canceller with an adaptive blocking matrix is used. The proposed adaptation mode controller can be used even when the adaptive blocking matrix is not adapted, and is much stable than the power ratio method. The proposed algorithm is evaluated in real environment, and simulation results show 13dB SINR improvement with the speaker sitting 2m distance from the may.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.463-464
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.710-711
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.453-454
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• 2010