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浙江大学学报(工学版)
浙江大学学报(工学版)  2019, Vol. 53 Issue (6): 1198-1204    DOI: 10.3785/j.issn.1008-973X.2019.06.020
计算机与自动化技术     
两级参考点匹配位置指纹声源定位方法
王硕朋1(),杨鹏1,2,*(),孙昊1,2,刘迈1
1. 河北工业大学 人工智能与数据科学学院，天津 300130
2. 教育部智能康复装置与检测技术工程研究中心，天津 300130
Fingerprint-based sound source localization method using two-stage reference points matching
Shuo-peng WANG1(),Peng YANG1,2,*(),Hao SUN1,2,Mai LIU1
1. School of Artificial Intelligence, Hebei University of Technology, Tianjin 300130, China
2. Smart recovery device and testing technology engineering research center of Ministry of Education, Tianjin 300130, China
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摘要：

提出一种两级参考点（RPs）匹配方法来减少位置指纹声源定位（SSL）过程中临近参考点搜索的计算量. 离线采样阶段：通过K均值聚类算法将数据库划分为一定数目的子库，并采用一种距离检测方法对离群点进行剔除. 在线定位阶段：通过第一级临近子库匹配完成对参考点搜索范围的缩减；在临近子库内进行第二级参考点匹配得到临近参考点；完成声源目标（TP）定位. 实验结果表明，采用两级参考点匹配算法可以在保证定位精度的前提下有效提高位置指纹声源定位方法的定位效率.
关键词： 声音位置指纹;  临近参考点;  K均值聚类算法;  两级参考点（RPs）匹配    
Abstract:

A two-stage matching method was proposed for computation reduction of adjacent reference points (RPs) searching in fingerprint-based sound source localization (SSL). In offline sampling phase, the K-means clustering method was adopted to divide the database into a certain number of sub-databases and the outliers were eliminated by the distance-based detection method. In online positioning phase, searching space was compressed by the first stage sub-database matching; then adjacent RPs were obtained through the second stage RPs matching in the adjacent sub-database; the auditory target point (TP) location estimation was accomplished. The experimental results show that the two-stage RPs matching algorithm can effectively improve the positioning efficiency of fingerprint-based sound source localization on the premise of ensuring the positioning accuracy.
Key words: sound-position fingerprint    adjacent reference points (RPs)    K-means clustering method    two-stage RPs matching
收稿日期: 2018-05-07 出版日期: 2019-05-22
CLC:  TP 181  
通讯作者: 杨鹏     E-mail: wangsp87921@hotmail.com;yphebut@163.com
作者简介: 王硕朋（1987—），男，博士生，从事听觉定位研究. orcid.org/0000-0001-7591-6874. E-mail： wangsp87921@hotmail.com
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引用本文:

王硕朋,杨鹏,孙昊,刘迈. 两级参考点匹配位置指纹声源定位方法[J]. 浙江大学学报(工学版), 2019, 53(6): 1198-1204.

Shuo-peng WANG,Peng YANG,Hao SUN,Mai LIU. Fingerprint-based sound source localization method using two-stage reference points matching. Journal of ZheJiang University (Engineering Science), 2019, 53(6): 1198-1204.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.06.020    或    http://www.zjujournals.com/eng/CN/Y2019/V53/I6/1198

图 1  基于位置指纹的声源定位（SSL）技术示意图
图 2  基于坐标空间的数据库划分方法
图 3  临近子库搜索过程
图 4  子库内临近参考点（RPs）搜索过程
图 5  听觉定位系统和实验场景
图 6  子库数目对定位的影响
数据库划分方式 NAM TAM / s δMA / m σ2/m2
无分区 72.0 0.027 1 0.094 5 0.006 9
坐标划分 22.3 0.008 4 0.121 4 0.009 8
特征聚类划分 21.7 0.008 1 0.081 3 0.003 9
表 1  不同数据库划分方式对定位效果的影响对比
图 7  子库数目为4时不同划分方式对定位的影响
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[1] 王硕朋, 杨鹏, 孙昊. 听觉定位数据库构建过程优化[J]. 浙江大学学报(工学版), 2018, 52(10): 1973-1979.