• Title/Summary/Keyword: Delay and sum Beamforming

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Wide Coverage Microphone System for Lecture Using Ceiling-Mounted Array Structure (천정형 배열 마이크를 이용한 강의용 광역 마이크 시스템)

  • Oh, Woojin
    • 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.

MVDR Beamformer for High Frequency Resolution Using Subband Decomposition (부대역을 이용한 MVDR 빔형성기의 주파수 분해능 향상 기법)

  • 이장식;박도현;김정수;이균경
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.1
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    • pp.62-68
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    • 2002
  • It is well known that the MDVR beamforming outperforms the conventional delay-sum beamformer in the sense of noise rejection and bearing resolution. However, the MDVR method requires long observation time to achieve high frequency resolution. The STMV method uses the steered covariance matrix of sensor data, so it has an ability to form an adaptive weight vector from a single time-series snapshot. But it uses the same weight vector across all frequencies. In this paper, we propose an SSMV method. The basic idea of the SSMV method is to decompose a full frequency band into several subbands to acquire a weight vector for each subband, individually. Also the wrap may be divided into several subarrays in order to reduce a computational load and the bandwidth of each subband. Simulations using real sea trial data show that the proposed SSMV method has good performance with short observation time.