• ETRI Journal
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• 제46권3호
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• pp.421-431
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• 2024

In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation of the noise subspace is performed according to the NC characteristics. Because the proposed method uses the signal information from the previous iteration, it can realize automatic data associations. Compared with traditional DPD and two-step localization methods, our novel process has lower computational complexity and provides higher accuracy. Moreover, its performance is better than that of the traditional tracking methods. Numerous simulation results support the superiority of our proposed method.

• 방송공학회논문지
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• 제23권4호
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• pp.519-525
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• 2018

본 논문에서는 다채널 위너 필터를 이용하여 마이크로폰 어레이에서 취득된 신호의 잡음을 제거하는 방법을 다룬다. 다채널 위너 필터는 음성 신호의 방향에 대한 정보를 필요로 하지 않는 필터로서 단일 음성 음원의 경우, 음성 왜곡을 발생시키지 않는 MVDR (Minimum Variance Distortionless Response) 공간 필터와 단일 채널 스펙트럼 필터로 분리될 수 있다. MVDR의 방향벡터에 해당하는 단일 음성 음원과 마이크로폰 어레이 간의 음향 전달 함수는 다채널 위너 필터의 부공간 분해 (subspace decomposition)를 이용하여 추정할 수 있다. 이 때 상관 행렬 추정 과정에서 발생하는 오차로 인해 추정되는 음향 전달 함수에도 오차가 발생하게 되며 이에 따라 다채널 위너 필터를 구성하는 MVDR은 음성 왜곡을 발생시키게 된다. 이러한 음성 왜곡을 완화시키기 위해 diagonal loading을 적용하고 실험을 통해 그 효과를 검증한다. 실험에서는 7개의 선형 마이크로폰으로 수집된 데이터를 이용하였으며 잡음을 섞기 전 신호와 잡음을 섞은 후 필터를 통과시킨 신호 간의 MFCC 오차를 측정한다. 실험 결과, diagonal loading을 통해 MFCC 오차를 줄일 수 있음을 확인하였다.

• ETRI Journal
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• 제34권5호
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• Journal of electromagnetic engineering and science
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• 제5권2호
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• pp.49-60
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• 2005

In this paper, an efficient performance enhancement scheme for an adaptive antenna array under the flat and the frequency-selective Rayleigh fadings is proposed. The proposed signal enhancement scheme is the modified linear signal estimator which combines the rank N approximation by reducing noise eigenvalues(RANE) and Toeplitz matrix approximation(TMA) methods into the linear signal estimator. The proposed performance enhancement scheme is performed by not only reducing the noise component from the signal-plus-noise subspace using RANE but also having the theoretical property of noise-free signal using TMA. Consequently, the key idea of the proposed performance enhancement scheme is to greatly enhance the performance of an adaptive antenna array by removing all undesired noise effects from the post-correlation received signal. The proposed performance enhancement scheme applies at the Wiener maximal ratio combining(MRC) method which has been widely used as the conventional adaptive antenna array. It is shown through several simulation results that the performance of an adaptive antenna array using the proposed signal enhancement scheme is much superior to that of a system using the conventional method under several environments, i.e., a flat Rayleigh fading, a fast frequency-selective Rayleigh fading, a perfect/imperfect power control, a single cell, and a multicell.

• 한국음향학회지
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• 제8권4호
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• pp.44-52
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• 1989

UCERSS (Unit Circle Eigendecomposition Rational Signal Subspace) 알고리듬은 MUSIC(MUltiple Signal Classification) 알고리듬을 2차원으로 확장하여 단위원 상에서의 eigendecomposition을 이용함으로써 다수의 광대역 신호의 입사각을 추정해 왔다. 이 논문의 목적은 신호대잡음비가 아주 낮은 경우에도 다수의 광대역 신호의 입사각을 추정할 수 있도록 UCERSS 알고리듬을 개선하는데 있다. 잡음 성분을 술이기 위해 covariance difference 행렬을 이용한 ESPRIT(Estimation of Signal Parameter via Rotational Invariance Technique) 알고리듬을 UCERSS 알고리듬과 결합하여 2차원으로 확장시킨 wide band ESPRIT 알고리듬을 제시하였다. 컴퓨터 시뮬레이션을 통하여 제시된 알고리듬의 성능을 UCERSS 알고리듬의 성능과 비교하여 제시된 알고리듬의 성능이 우수함을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• 한국항행학회논문지
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• 제24권1호
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• pp.47-52
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• 2020

도래각추정은 표적으로부터 생성, 혹은 반사된 신호를 분석하여 표적의 방향을 추정하는 것으로 다양한 분야에 활용되고 있다. 인공신경망은 생물의 신경망을 모방한 기계학습의 한 분야로 패턴인식에서 좋은 성능을 보인다. 이러한 인공신경망을 도래각 추정에 활용하는 연구가 진행되어왔으나, 다양한 신호대잡음비 환경에 대응하는데에 제한이 있는 상황이다. 본 논문에서는 도래각 추정을 위한 3단계 인공신경망 알고리듬을 제안한다. 제안하는 알고리듬은 잡음제거과정을 통해 단일 신호대잡음비 환경에서 학습한 모델을 다양한 환경에 적용해도 성능감소를 최소화할 수 있다. 또한 도래각 시프트 과정을 통해 학습 난이도를 낮출 수 있고 효율적인 추정이 가능하다. 우리는, 제안하는 알고리듬과 다른 부공간 기법, Cramer-Rao bound (CRB)와의 성능 비교를 통해 제안하는 알고리듬이 낮은 신호대잡음비 환경, 표적들의 도래각이 가까운 환경 등 특정한 열악한 관측환경에서 타 기법에 비해 좋은 성능을 보이는 것을 확인하였다.

• 한국멀티미디어학회논문지
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• 제19권7호
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• pp.1127-1136
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• 2016

Speech enhancement algorithm plays an important role in numerous speech signal processing applications. Over the last few decades, many algorithms have been studied for speech enhancement. The algorithms are based on spectral subtraction, Wiener filter, and subspace method etc. They have good performance of speech enhancement, but the performance can be deteriorated in specific noises or low SNR environment. In this paper, a new speech enhancement algorithms are proposed based on adaptive noise canceller. And the proposed algorithm improved performance of adaptive noise cancelling using 2-D binary mask. From objective experimental index, it is confirmed that the proposed algorithm is useful and has better performance than recently proposed speech enhancement algorithms.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.348-351
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• 2007

This paper investigates the natural modes of moduled floating structure with module unit connector. As an example structure, a floating parking place($120m{\times}60m$) is considered. In the evaluation of natural modes, numerical equations are formulated by FEM(Finite Element Method) and the natural modes are solved by the subspace iteration method. By comparing results for various stiffness of module unit connector, the effect of stiffness of unit connector is examined.

• 한국소음진동공학회논문집
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• 제18권3호
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• pp.356-360
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• 2008

This paper investigates the natural modes of moduled floating structure with module unit connector. As an example structure, a floating parking place($120m\;{\times}\;60m$) is considered. In the evaluation of natural modes, numerical equations are formulated by FEM(finite element method) and the natural modes are solved by the subspace iteration method. By comparing results for various sizes of module unit, the effect of unit size is investigated. By comparing results for various stiffness of module unit connector, the effect of stiffness of unit connector is also examined.