• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.395-402
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• 2016

In this paper, a wideband adaptive beamforming approach for an acoustic vector sensor linear array is presented. It is a very important issue to estimate the stable covariance matrix for adaptive beamforming. In the conventional wideband adaptive beamforming based on coherent signal-subspace (CSS) processing, the error of bearing estimates is resulted from the focusing matrix estimation and the large number of data snapshot is necessary. To alleviate the estimation error and snapshot deficiency in estimating covariance matrix, the steered covariance matrix method in the pressure sensor is extended to the vector sensor array, and the subarray technique is incorporated. By this technique, more accurate azimuth estimates and a stable covariance matrix can be obtained with a small number of data snapshot. Through simulation, the azimuth estimation performance of the proposed beamforming method and a wideband adaptive beamforming based on CSS processing are assessed.

• The Journal of the Acoustical Society of Korea
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• v.12 no.2E
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• pp.47-62
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• 1993

SMI 방법은 수치적인 불안정성과 아울러 많은 계산량을 갖는다. 본 논문에서는 역 공분산 행렬의 Cholesky 분할을 이용하여 SMI 방법보다 효율적인 방법을 제안한다. 제안한 방법에서는 적응 빔 형상과 검출이 하나의 구조로 실현되며 이에 피룡한 역 공분산 행렬의 Cholesky factor는 secondary 입력으로부터 GS 프로세서를 이용하여 추정한다. 제안한 구조의 중요한 특징은 공분산 행렬과 Cholesky factor를 직접 구할 필요가 없다는 점이며, 또한 GS 프로세서의 장점을 이용한 systolic 구조를 사용함으로써 효율적인 계산을 수행할 수 있다. 모의 실험을 통하여 제안한 방법의 성능과 SMI 방법의 성능을 서로 비교하였다. 또한 nonhomogeneous 환경에서 동작하기 위한 방법이 제시되었으며, 아울러 계산량이 많은 GS 구조의 단점을 극복하기 위해 lattice-GS 구조를 이용하는 방법을 제안하였다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.94-100
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• 2001

When using a sample covariance matrix data in paucity of snapshots, adaptive matched field processing will have problem in inverting covariance matrix due to the rank deficiency. The general solutions are diagonal loading and eigenanalysis methods, but there is a significant bias in the power output. This paper presents a quantitative study of bias of power output and the performance of source localization through the simulation and the measured data analysis in fixed source case using the diagonal loading method for the minimum variance processor. Results show that the bias in power output is reduced and the performance of source localization is improved when the number of snapshots is greater than the number of array sensors.

• The Journal of the Acoustical Society of Korea
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• v.33 no.5
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• pp.326-334
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• 2014

This paper proposes a novel covariance matrix estimation scheme for minimum variance distortionless response (MVDR) beamforming. By accurately tracking direction-of-sound source arrival (DoA) information using audio-visual sensors, the covariance matrix is efficiently estimated by adopting a variable forgetting factor. The variable forgetting factor is determined by considering signal-to-interference ratio (SIR). Experimental results verify that the performance of the proposed method is superior to that of the conventional one in terms of interference/noise reduction and speech distortion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.939-951
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• 1994

In adaptive equalizers based on least mean squares (LMS) algorithms, the convergence rate is determined by the convariance matrix of an input signal. When the eigenvalue spread of the convariance matrix is close to unity, the convergence rate is quite fast. In this paper, for fast convergence of LMS-based adaptive equalizers we propose a modified reference signal pertinent to the statistical channel. From the theoretical analysis and computer simulation, it is shown that the proposed modification method is quite effective for fast convergence of LMS-based adaptive equalizers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11B
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• pp.1510-1521
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• 2001

In this paper a subspace-based blind interference cancellation is proposed and its performance is analyzed. Then the blind adaptive implementation is devolped using the improved natural power method which is the signal subspace tracking algorithm. The theoretical analysis shows that when the exact covariance matrix is kown the performance of the proposed detector is the same as that of the decorrelating detector. And when the covariance matrix is estimated the asymptotic results are examined. The results of computer simulation demonstrate that the proposed detector outperforms the previous blind adaptive RLS MOE detector.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.315-323
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• 2011

This paper proposes two methods of estimating prior distribution to improve the performance of rapid speaker adaptation based on maximum a posteriori linear regression (MAPLR). In general, prior distribution of the transformation matrix used in MAPLR adaptation is estimated from all of the training speakers who are employed to construct the speaker-independent model, and it is applied identically to all new speakers. In this paper, we propose a method in which prior distribution is estimated from a group of reference speakers, selected using adaptation data, so that the acoustic characteristics of the selected reference speakers may be similar to that of the new speaker. Additionally, in MAPLR adaptation with block-diagonal transformation matrix, we propose a method in which the mean matrix and covariance matrix of prior distribution are estimated from two groups of transformation matrices obtained from the same training speakers, respectively. To evaluate the performance of the proposed methods, we examine word accuracy according to the number of adaptation words in the isolated word recognition task. Experimental results show that, for very limited adaptation data, statistically significant performance improvement is obtained in comparison with the conventional MAPLR adaptation.

• The Journal of the Acoustical Society of Korea
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• v.10 no.6
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• pp.71-76
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• 1991

적응 어레이 시스템에서 최적해에 도달하기 위한 계수들의 수렴 속도는 공분산 행렬의 고유치 분포율에 의해 지배된다. 본 논문에서는 우선 GSC의 고유치 분포율을 구하였다. 또한 conherent 상황에 서 GSC의 출력 파워 식을 유도하였다.

• ICROS
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• v.3 no.5
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• pp.43-50
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• 1997

이 글에서는 이진 증류탑을 위한 적응 제어 기법에 대해 소개하였다. 제안된 방법은 최근 개발된 다변수 예측 제어 알고리즘과 공분산 행렬 정규화 기능을 갖는 추정 알고리즘에 기초하고 있다. 이러한 적응 시스템은 그 설계과정이 복잡하지 않아 실저적 적용 가능성이 높다는 점에서 가치가 있다. 필터를 제외하면 단 두 개의 제어기 상수만이 결정되면 되고, 더욱이 이들이 공정의 상승 및 정정 시간과 관련되어 그 설정이 쉽다는 중요한 특징을 갖는다. 이와 같은 제어기 설계의 간소화에도 불구하고 증류탑의 설정값 추종 성능 및 Feed 변화에 대한 제어 성능의 우수함을 공정 모사를 통해 확인하였다.