• The Journal of the Acoustical Society of Korea
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• v.24 no.1E
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• pp.34-37
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• 2005

Ryu et al. proposed a multiple target angle-tracking algorithm without a data association problem using angular innovations. This algorithm, however, needs the computational loads in proportion to the square number of sensors regardless of the number of targets, because it uses a nonlinear equation between the signal subspace and angular innovation. In this Paper, we proposed an efficient algorithm for the multiple target angle-tracking using angular innovations. The proposed algorithm extracts the angular innovations from noise subspace. Also, it is demonstrated by computer simulations dealing with the tracking of crossing targets. The simulation results show that the computational loads of the proposed algorithm are $80\%$ and $60\%$ of those of Ryu's algorithm for 3 targets and 6 targets without degrading the performance of the target tracking.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.75-78
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• 1997

In this paper we present new sound spectral analysis methods or prosthetic heart valve sounds. Phonocardiograms(PCG) of prosthetic heart valve were analyzed in order to derive frequency domain feature suitable or the classification of the valve state. The fast orthogonal search method and MUSIC (MUltiple SIgnal Classification) method are described or finding the significant frequencies in PCG. The fast orthogonal search method is effective with short data records and cope with noisy, missing and unequally-spaced data. MUSIC method's key to the performance is the division of the information in the autocorrelation matrix or the data matrix into two vector subspaces, one a signal subspace and the other a noise subspace.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.262-267
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• 1998

In Synthetic Aperture Radar(SAR) imaging, the echoed data are collected by moving radar's position with respect to the target area, and this operation actually gives effect of synthesizing aperture size, which in turn gives better cross range resolution of reconstructed target scene. Among several inversion scheme for SAR Imaging, we uses an inversion scheme which uses no approximation in wave propagation analysis, and try to verify whether the collected data with synthesized aperture actually gives the same support as that with physical aperture in the same size. To do this, we make a signal subspace comparison of two imaging models with physical and synthesized arrays, respectively. Theoretical comparison and numerical analysis using Gram-Schmidt procedures had been performed. The results showed that the synthesized array data fully span the physical array data with the same system geometry and strongly support the proposed inversion scheme valuable in high resolution radar imaging.

• ETRI Journal
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• v.46 no.3
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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.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.392-392
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• 2004

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.703-719
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• 2011

In multi-user wireless communication systems, adaptive modulation and scheduling are promising techniques for increasing the system throughput. However, a mass of wireless recourse will be occupied and spectrum efficiency will be decreased to feedback channel quality indication (CQI) of all users in every subcarrier or chunk for adaptive orthogonal frequency division multiplexing (OFDM) systems. Thus numerous limited feedback schemes are proposed to reduce the system overhead. The recently proposed compressive sensing (CS) theory provides a new framework to jointly measure and compress signals that allows less sampling and storage resources than traditional approaches based on Nyquist sampling. In this paper, we proposed two novel CQI feedback schemes based on general CS and subspace CS, respectively, both of which could be used in a wireless OFDM system. The feedback rate with subspace CS is greatly decreased by exploiting the subspace information of the underlying signal. Simulation results show the effectiveness of the proposed methods, with the same feedback rate, the throughputs with subspace CS outperform the discrete cosine transform (DCT) based method which is usually employed, and the throughputs with general CS outperform DCT when the feedback rate is larger than 0.13 bits/subcarrier.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.6
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• pp.1-8
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• 2001

Recently, Ryu et al. proposed a multiple target angle tracking algorithm using the angular innovation extracted from the estimated signal subspace. This algorithm obtains the angles of targets and associates data simultaneously. Therefore, it has a simple structure without data association problem. However it requires the calculation of the inverse of a real matrix with dimension (2N+1)${\times}$(2N+1) to obtain the angular innovations of N targets. In this paper, a new linear equation for angular innovation is proposed using the fact that the projection error is zero when the target steering vector is projected onto the signal subspace. As a result, the proposed algorithm dose not require the matrix inversion and is computationally efficient.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.305-309
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• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.515-523
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• 1997

A high resolution algorithm is presented for resolving multiple coherent spread spectrum signals that are incident on an equispaced linear array. Unlike the conventional noise-eigenvector based methods, this algorithm makes use of the signal eigenvectors of the array spectral density matrix that are associates with eigenvalues that are larger than the sensor noise level. Simulation results are shown to demonstate the high performance of the proposed approach in comparison with MUSIC in which coherent signal subspace method (CSM) is employed.