• Title/Summary/Keyword: DOA

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Multiple Target DOA Tracking Algorithm Using Measurement Fusion (측정치 융합기법을 이용한 다중표적 방위각 추적 알고리즘)

  • 신창홍;류창수;이균경
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.493-496
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    • 2003
  • Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

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Spatially Close Signals Separation via Array Aperture Expansions and Spatial Spectrum Averaging

  • Kang, Heung-Yong;Kim, Young-Su;Kim, Chang-Joo
    • ETRI Journal
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    • v.26 no.1
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    • pp.45-47
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    • 2004
  • A resolution enhancement method for estimating the direction-of-arrival (DOA) of signals is presented. The proposed method is by virtually expanding a real array into virtual arrays and then averaging the spatial spectrum of the virtual arrays, each of which has a different aperture size. Superior DOA resolutions are shown in comparison with the standard algorithm, MUltiple SIgnal Classification (MUSIC), for incoherent signals incident on a uniform circular array.

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The DOA Estimation of Wide Band Moving Sources

  • Cho, Mun-Hyeong
    • Journal of information and communication convergence engineering
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    • v.5 no.1
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    • pp.12-16
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    • 2007
  • In this paper, a new method is proposed for tracking the direction-of-arrival (DOA) of the wideband moving source incident on uniform linear array sensors. DOA is estimated by focusing transformation matrices. To update focusing matrices along with new data snap shots, we use the FAST (Fast Approximate Subspace Tracking) method. Present focusing matrices are constructed by previous signal and its orthogonal basis vectors as well as present signal and its orthogonal basis vectors, which are the left and right singular vectors of the inner product of two approximated matrices. Simulation results are shown to illustrate the performance of the proposed method.

DOA Estimation of New Appearing Source in Wideband Multisource Beamforming with Array Sensor Position Calibration Algorithm (어레이 센서 위치보정 알고리즘을 적용한 광대역 다중 신호원 빔형성에서 새로운 신호원의 도래방향 추정)

  • 심재광;강성현;윤원식
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.3
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    • pp.49-54
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    • 1999
  • In this paper, we propose a new method to estimate the initial DOA of a new appearing source in wideband multisource beamforming and tacking with array sensor position calibration algorithm. By using a beampattern formula for initial DOA detection, the proposed method keeps estimation error within possible tracking range and can be applied to several beamformers with different mainlobe width by adjusting DOA resolution. The simulation results show the performances of source detection and tracking.

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Model-based Clustering of DOA Data Using von Mises Mixture Model for Sound Source Localization

  • Dinh, Quang Nguyen;Lee, Chang-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.59-66
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    • 2013
  • In this paper, we propose a probabilistic framework for model-based clustering of direction of arrival (DOA) data to obtain stable sound source localization (SSL) estimates. Model-based clustering has been shown capable of handling highly overlapped and noisy datasets, such as those involved in DOA detection. Although the Gaussian mixture model is commonly used for model-based clustering, we propose use of the von Mises mixture model as more befitting circular DOA data than a Gaussian distribution. The EM framework for the von Mises mixture model in a unit hyper sphere is degenerated for the 2D case and used as such in the proposed method. We also use a histogram of the dataset to initialize the number of clusters and the initial values of parameters, thereby saving calculation time and improving the efficiency. Experiments using simulated and real-world datasets demonstrate the performance of the proposed method.

Multiple Target DOA Tracking Algorithm With Measurement Fusion Based on ML (ML 기법에 기반을 둔 측정치 융합기법을 가진 다중표적 방위각 추적 알고리즘)

  • Ryu, Chang-Soo;Park, Ju-Tae;Choi, Sung-Un
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.3
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    • pp.177-183
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    • 2003
  • Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

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DOA-based Beamforming for Multi-Cell Massive MIMO Systems

  • Hu, Anzhong
    • Journal of Communications and Networks
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    • v.18 no.5
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    • pp.735-743
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    • 2016
  • This paper proposes a direction-of-arrival (DOA)-based beamforming approach for multi-cell massive multiple-input multiple-output systems with uniform rectangular arrays (URAs). The proposed approach utilizes the steering vectors of the URA to form a basis of the spatial space and selects the partial space for beamforming according to the DOA information. As a result, the proposed approach is of lower computational complexity than the existing methods which utilize the channel covariance matrices. Moreover, the analysis demonstrates that the proposed approach can eliminate the interference in the limit of infinite number of the URA antennas. Since the proposed approach utilizes the multipaths to enhance the signal rather than discarding them, the proposed approach is of better performance than the existing low-complexity method, which is verified by the simulation results.

DOA Estimation of Arrays Antenna using Second Order Statistics (2차 통계량을 이용한 배열 안테나의 도래 방향 추정)

  • Byon Kun-Sik;Jang Eun-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.3
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    • pp.522-527
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    • 2005
  • We need a transmission of high quality and capacity according to a fast supply of mobile communication terminal. As multipath fading occured in high speed transmission, adaptive array antenna habe been studied to solve such a demand. DOA(Direction of Arrival) estimation play a important .ole in adaptive a..ay antenna. This paper present a space time blind identification using second order statistics and present blind space time adaptive array antenna. Also we verified a effect of the presented method.

Computationally Efficient 2-D DOA Estimation Using Two Parallel Uniform Linear Arrays

  • Cao, Hailin;Yang, Lisheng;Tan, Xiaoheng;Yang, Shizhong
    • ETRI Journal
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    • v.31 no.6
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    • pp.806-808
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    • 2009
  • A new computationally efficient algorithm-based propagator method for two-dimensional (2-D) direction-of-arrival (DOA) estimation is proposed, which uses two parallel uniform linear arrays. The algorithm takes advantage of the special structure of the array which enables 2-D DOA estimation without pair matching. Simulation results show that the proposed algorithm achieves very accurate estimation at a computational cost 4 dB lower than that of standard methods.

Wideband DOA Estimation with FDFIB Network (FDFIB Network를 이용한 광대역 DOA 추정)

  • Zhou, Weiwei;Wang, Yisu;Jang, Woo-Jin;Koh, Jin-Hwan
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.251-252
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    • 2006
  • In this paper, we presented an extension of the broadband DOA estimation method using frequency-domain frequency-invariant beamforming (FDFIB). The technique uses FDFIB instead of conventional frequency invariant beamforming (FIB) methods. And different narrowband DOA estimation methods, MUSIC, ESPRIT, and MPM, are used respectively. A comparison is made to demonstrate that the FDFIB-MPM not only offers a better resolution than the FDFIB-MUSIC, FDFIB-ESPRIT, but also it is computationally very efficient.

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