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一种基于高阶广义奇异值分解估计多个声源方向的高效框架。

An Efficient Framework for Estimating the Direction of Multiple Sound Sources Using Higher-Order Generalized Singular Value Decomposition.

作者信息

Suksiri Bandhit, Fukumoto Masahiro

机构信息

Department of Engineering, Graduate School of Engineering, Kochi University of Technology, Kami Campus, Kochi 782-0003, Japan.

School of Information, Kochi University of Technology, Kami Campus, Kochi 782-0003, Japan.

出版信息

Sensors (Basel). 2019 Jul 5;19(13):2977. doi: 10.3390/s19132977.

DOI:10.3390/s19132977
PMID:31284497
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6651797/
Abstract

This paper presents an efficient framework for estimating the direction-of-arrival (DOA) of wideband sound sources. The proposed framework provides an efficient way to construct a wideband cross-correlation matrix from multiple narrowband cross-correlation matrices for all frequency bins. In addition, the proposed framework is inspired by the coherent signal subspace technique with further improvement of linear transformation procedure, and the new procedure no longer requires any process of DOA preliminary estimation by exploiting unique cross-correlation matrices between the received signal and itself on distinct frequencies, along with the higher-order generalized singular value decomposition of the array of this unique matrix. Wideband DOAs are estimated by employing any subspace-based technique for estimating narrowband DOAs, but using the proposed wideband correlation instead of the narrowband correlation matrix. It implies that the proposed framework enables cutting-edge studies in the recent narrowband subspace methods to estimate DOAs of the wideband sources directly, which result in reducing computational complexity and facilitating the estimation algorithm. Practical examples are presented to showcase its applicability and effectiveness, and the results show that the performance of fusion methods perform better than others over a range of signal-to-noise ratios with just a few sensors, which make it suitable for practical use.

摘要

本文提出了一种用于估计宽带声源到达方向(DOA)的高效框架。所提出的框架提供了一种有效的方法,可从所有频率 bins 的多个窄带互相关矩阵构建宽带互相关矩阵。此外,所提出的框架受相干信号子空间技术的启发,并对线性变换过程进行了进一步改进,新过程不再需要通过利用接收信号与其自身在不同频率上的独特互相关矩阵以及该独特矩阵阵列的高阶广义奇异值分解来进行 DOA 初步估计的任何过程。通过采用任何基于子空间的技术来估计窄带 DOA,但使用所提出的宽带相关性而非窄带相关矩阵,来估计宽带 DOA。这意味着所提出的框架使近期窄带子空间方法中的前沿研究能够直接估计宽带源的 DOA,从而降低计算复杂度并简化估计算法。给出了实际示例以展示其适用性和有效性,结果表明融合方法的性能在一系列信噪比下仅使用少数传感器时比其他方法表现更好,这使其适用于实际应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/c97e956ef26f/sensors-19-02977-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/e3fdf34c1123/sensors-19-02977-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/236fb4e5295a/sensors-19-02977-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/ce7400230f85/sensors-19-02977-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/a2551cefa088/sensors-19-02977-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/d0cbf750b44c/sensors-19-02977-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/5f6e55876aba/sensors-19-02977-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/0905a2846b8c/sensors-19-02977-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/87a8842e57af/sensors-19-02977-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/51e6082564f1/sensors-19-02977-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/1774ca21033c/sensors-19-02977-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/c97e956ef26f/sensors-19-02977-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/e3fdf34c1123/sensors-19-02977-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/236fb4e5295a/sensors-19-02977-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/d0cbf750b44c/sensors-19-02977-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/5f6e55876aba/sensors-19-02977-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/0905a2846b8c/sensors-19-02977-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/87a8842e57af/sensors-19-02977-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/1774ca21033c/sensors-19-02977-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cef/6651797/c97e956ef26f/sensors-19-02977-g011.jpg

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3
Joint Estimation of DOA and Frequency of Multiple Sources with Orthogonal Coprime Arrays.
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Sensors (Basel). 2019 Jan 15;19(2):335. doi: 10.3390/s19020335.
4
A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.一种针对车辆连续运动事件的稳健实时到达方向估计方法。
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5
Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments.用于室外环境声源定位的无人机嵌入式麦克风阵列系统设计
Sensors (Basel). 2017 Nov 3;17(11):2535. doi: 10.3390/s17112535.
6
A Low-Complexity Method for Two-Dimensional Direction-of-Arrival Estimation Using an L-Shaped Array.一种使用L型阵列进行二维到达方向估计的低复杂度方法。
Sensors (Basel). 2017 Jan 19;17(1):190. doi: 10.3390/s17010190.
7
Acoustical Direction Finding with Time-Modulated Arrays.基于时间调制阵列的声学测向
Sensors (Basel). 2016 Dec 11;16(12):2107. doi: 10.3390/s16122107.
8
SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization.声罗盘:一种基于分布式 MEMS 麦克风阵列的声源定位传感器。
Sensors (Basel). 2014 Jan 23;14(2):1918-49. doi: 10.3390/s140201918.
9
Source localization with acoustic sensor arrays using generative model based fitting with sparse constraints.基于生成模型拟合和稀疏约束的声传感器阵列源定位。
Sensors (Basel). 2012 Oct 15;12(10):13781-812. doi: 10.3390/s121013781.
10
Olfaction and hearing based mobile robot navigation for odor/sound source search.基于嗅觉和听觉的移动机器人导航用于气味/声源搜索。
Sensors (Basel). 2011;11(2):2129-54. doi: 10.3390/s110202129. Epub 2011 Feb 11.