• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.19-25
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• 2003

Ryu et al. recently proposed a multiple target angle-tracking algorithm without a data association problem. This algorithm, however, shows the degraded performance on evasive maneuvering targets, because the estimated signal subspace is d,:graded in the algorithm. In this Paper, we proposed a new algorithm, in which VFF-PASTd (Variable Forgetting Factor PASTd) algorithm is applied to Ryu's algorithm to effectively handle the evasive target tracking with better time-varying signal subspace.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.37-40
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• 2000

기존의 신호 공간 추적 방법을 이용한 blind multiuser detector는 nonstationary 환경에서 새로운 환경에 적응하기 위해 비교적 긴 시간을 필요로 한다 본 논문은 가변 망각 인자를 도입한 확장 PASTd (Projection Approximation Subspace Tracking with Deflation) 알고리즘을 이용하여 환경 변화에 좀더 신속히 적응하는 성능 향상을 모의실험을 통해 보이고자 한다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1E
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• pp.7-13
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• 2001

In this paper we propose a new subspace tracking algorithm based on the PASTd (Projection Approximation Subspace Tracking with deflation). The algorithm is obtained via introducing the variable forgetting factor which adapts itself to the time-varying subspace environments. The tracking capability of the proposed algorithm is demonstrated by computer simulations in an abruptly changing DOA scenario. The estimation results of the variable forgetting factor PASTd(VFF-PASTd) outperform those of the PASTd in the nonstationary case as well as in the stationary case.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.189-192
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• 2000

본 논문은 Nonstationary 환경에서 동작하는 소나의 DOA추정의 정확도를 높이기 위하여 가변 망각인자를 도입한 새로운 Extended PASTd (Extended Projection Approximation of Subspace Tracking with deflation) 을 제안하고 기존 알고리즘과 비교함으로써 새로운 알고리즘의 향상된 성능을 보인다.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.179-182
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• 2001

본 논문에서는 기존의 VFF PASTd 알고리듬의 개선안을 제시하였다. 이 알고리듬은 각 부공간마다 가변망각인자를 각각 사용하던 기존 방법과는 달리 최종 잔류 오차를 이용하여 하나의 망각인자를 계산하고 이것을 이용함으로써 계산량을 줄임과 동시에 망각인자를 보다 정확히 구할 수 있다. 여기서는 주파수 추정 문제에 대한 모의 실험을 통해 제안된 알고리듬이 우수함을 입증하였다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.218-218
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• 2004

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.237-240
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• 2002

지면에 가까이 있는 비행체나 수면에 가까이 있는 수중 운동체에서 도래하는 신호는 직접파와 반사파로 구성되어 있다. 그런 환경에서는 반사파가 직접파와 coherent한 관계를 갖는다. 이런 현상으로 해서 DOA추정을 위해 추정한 correlation 행렬이 singular한 성질을 갖게 된다. 이렇게 singular한 행렬은 DOA추정에 큰 오류를 내게 된다. 또 움직이는 대상의 경우 추정 correlation 행렬의 성질이 시간에 따라 변하게 된다. 본 논문에서는 위 두 상황을 함께 해결하기 위해서 PASTd알고리즘을 변형하여 Forward/Backward Variable forgetting factor를 도입한 PASTd알고리즘을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.162-170
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• 2010

Adaptive arrays reject interferences while preserving the desired signal, exploiting a priori information on its arrival angle. Subspace-based adaptive arrays, which adjust their weight vectors in the signal subspace, have the advantages of fast convergence and robustness to steering vector errors, as compared with the ones in the full dimensional space. However, the complexity of theses subspace-based methods is high because the eigendecomposition of the covariance matrix is required. In this paper, we present a simple subspace-based method based on the PASTd (projection approximation subspace tracking with deflation). The orignal PASTd algorithm is modified such that eigenvectora are orthogonal to each other. The proposed method allows us to significantly reduce the computational complexity, substantially having the same performance as the beamformer with the direct eigendecomposition. In addition to the simple beamforming method, we present theoretical analyses on the SINR (signal-to-interference plus noise ratio) of subspace beamformers to see their behaviors.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.148-156
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• 2014

In the MVDR (minimum variance distortionless response) adaptive array, its performance could be greatly deteriorated in the presence of steering vector errors as the desired signal is treated as an interference. This paper suggests an computationally simple adaptive beamforming method which is robust against these errors. In the proposed method, a minimization problem that is formulated according to the DCB (doubly constrained beamforming) principle is solved to find a solution vector, which is in turn projected onto a subspace to obtain a new steering vector. The minimization problem and the subspace projection are dealt with using some principal eigenpairs, which are obtained using a modified PASTd(projection approximation subspace tracking with deflation). We improve the existing MPASTd(modified PASTd) algorithm such that the computational complexity is reduced. The proposed beamforming method can significantly reduce the complexity as compared with the conventional ones directly eigendecomposing an estimate of the corelation matrix to find all eigenvalues and eigenvectors. Moreover, the proposed method is shown, through simulation, to provide performance improvement over the conventional ones.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.216-221
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• 2010

In this paper, we propose and develop a new algorithm for the principle subspace tracking by orthonormalizing the eigenvectors using an approximation of Gram-Schmidt procedure. We carry out a novel mathematical derivation to show that when this approximated version of Gram-Schmidt procedure is added to a modified form of projection approximation subspace tracking deflation (PASTd) algorithm, the eigenvectors can be orthonormalized within a linear computational complexity. While the PASTd algorithm tries to extracts orthonormalized eigenvectors, the new scheme orthonormalizes the eigenvectors after their extraction, yielding much more tacking efficiency. We apply the new tracking scheme for blind adaptive multiuser detection for non-stationary cellular CDMA environment and use extensive simulation results to demonstrate the performance improvement of the proposed scheme.