• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.609-612
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• 2000

본 논문에서는 음원에 관한 정보가 미지의 상황에서 마이크로폰 어레이를 사용하여 두 음원신호를 분리하는 ,시스템을 제안한다 이 시스템은 두 단계로 구성되어 있으며, 첫 번째 단계에서는 파워가 큰 제 1음원의 DOA(Direction Of Arrival)를 추정하고, AMUSE(Algorithm for Multiple Unknown Signals Extraction)법을 사용한 Blind Deconvolution에 의해 음원신호의 분리를 행한다 두 번째 단계에서는 파워가 낮은 제 2음원의 강조신호를 사용하여 DSA(Delay and Sum Array)법에 의해 제 2음원의 DOA를 추정하고,AMUSE법의 출력신호와 두 음원의 DOA를 이용하여 ANF(Adaptive Notch Filter)를 구성하고, 두 음원신호의 재 분리를 행한다. 그리고, 시뮬레이션을 통해 제안한 방법의 유효성을 검토한 결과 두 음원 신호가 분리 가능한 것이 확인되었다.

• ETRI Journal
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• v.43 no.5
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• pp.869-880
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• 2021

Herein, we estimate the direction of arrival (DOA) of non-Gaussian signals for nested arrays (NAs) by implementing the fourth-order difference co-array (FODC) and successive methods. In particular, considering the property of the fourth-order cumulant (FOC), we first construct the FODC of the NA, which can obtain O(N⁴) virtual elements using N physical sensors, whereas conventional FOC methods can only obtain O(N²) virtual elements. In addition, the closed-form expression of FODC is presented to verify the enhanced degrees of freedom (DOFs). Subsequently, we exploit the vectorized FOC (VFOC) matrix to match the FODC of the NA. Notably, the VFOC matrix is a single snapshot vector, and the initial DOA estimates can be obtained via the discrete Fourier transform method under the underdetermined correlation matrix condition, which utilizes the complete DOFs of the FODC. Finally, fine estimates are obtained through the spatial smoothing-Capon method with partial spectrum searching. Numerical simulation verifies the effectiveness and superiority of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.189-194
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• 2006

In this paper, design of MUSIC algorithm, which is one of high resolution DOA (direction of arrival) estimation techniques was studied. Generally the complex-valued correlation matrix of MUSIC algorithm is transformed to unitary matrix or matrix expansion for the real hardware implementation. Using the orthogonality between the noise subspace eigenvectors and the steering vectors corresponding to signal component, we estimate DOA with the real-valued computation between steering vectors and noise subspace eigenvectors. The DOA algorithm was designed with VHDL models with considerations of 2 elements and 1 incident wave and its simulation results are derived.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10A
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• pp.988-995
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• 2006

In this Paper, we Present a nonharmonic may geometry design method using Euclidan minimum distance function in difference Phase spaces for 2-D (azimuth/elevation) multiple baseline antenna may which has a way to reduce the number of sensor antennas while maintaining accurate DOA estimate. The major advantages of our approach is that even the shortest interelement spacing can be larger than half-wavelength and is not limit13d to linear and it can be applied successfully to any array configuration. In multiple signals impinging situation, the performance simulation results of superresolution algorithms shows the effectiveness of the proposed method. Also the 2-D asymmetric may using the Proposed method is designed and the Performance of the manufactured away through the experimental test is verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.48-59
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• 2000

Eigendecomposition based direction-of-arrival(DOA) estimation algorithm such as MUSIC(multiple signal classification) is known to perform well and provide high resolution in white noise environment. However, its performance degrades severely when the noise process is not white. In this paper we consider the DOA estimation problem in a colored noise environment as a problem of extracting periodic signals from noise, and we take the problem to the wavelet domain. Covariance matrix of multiscale components which are obtained by taking wavelet decomposition on the noise has a special structure which can be approximated with a banded sparse matrix. Compared with noise the correlation between multiscale components of narrowband signal decays slowly, hence the covariance matrix does not have a banded structure. Based on this fact we propose a DOA estimation algorithm that transforms the covariance matrix into wavelet domain and removes noise components located in specific bands. Simulations have been carried out to analyze the proposed algorithm in colored noise processes with various correlation properties.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.1
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• pp.15-23
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• 2003

This paper proposes a fast direction of arrival (DOA) estimation algorithm that can rapidly estimate incidence angles of incoming signals using a pseudo covariance matrix. The conventional subspace DOA estimation methods such as MUSIC (multiple signal classification) algorithms need many sample signals to acquire covariance matrix of input signals. Thus, it is difficult to estimate the DOAs of signals because they cannot perform DOA estimation during receiving sample signals. Also if the D0As of signals are changing rapidly, conventional algorithms cannot estimate incidence angles of signals exactly. The proposed algorithm obtains bearing response and directional spectrum after acquiring pseudo covariance matrix of each snapshot. The incidence angles can be exactly estimated by using the bearing response and directional spectrum. The proposed DOA estimation algorithm uses only concurrent snapshot so as to obtain covariance matrix. Compared to conventional DOA estimation methods. The proposed algorithm has an advantage that can estimate DOA of signal rapidly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2777-2784
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• 2011

In this paper, DOA(direction of arrival) of multiple incident signals received from linear array antenna and circular array antenna, which is based on nonparametric estimation algorithm, and adaptive beam-forming algorithm are studied and analyzed. In nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Especially, the discrimination ability of DOA and the adaptive beam-forming ability according to antenna array methods and the number of array elements are compared and considered.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.4
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• pp.388-394
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• 2016

There have been many studies on the direction-of-arrival(DOA) estimation algorithm using antenna arrays. Beamforming, Capon's method, maximum likelihood, MUSIC algorithms are the main algorithms for the DOA estimation. Recently, compressive sensing-based DOA estimation algorithm exploiting the sparsity of the incident signals has attracted much attention in the signal processing community. In this paper, the performance of the L1-SVD algorithm, which is based on fitting of the data matrix, is compared with that of the MUSIC algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.1-6
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• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.89-93
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• 2013

This paper is estimating a target direction of arrival with incident to receiver in spatial. This paper presented covariance using constraint matrix to correlation interference signal cancellation in multi input multi output array antennas system. we proposed a target direction of arrival estimation algorithm using cost function and minimum variance method. Through simulation, we were analysis a performance to compare general SPT-LCMV algorithm and proposal algorithm. We showed that proposal algorithm improve more target estimation than general SPT-LCMV algorithm in direction of arrival.