通信学报2017，Vol.38Issue(1)：106-116,11.DOI:10.11959/j.issn.1000-436x.2017013
基于近似核密度估计的近场多声源定位算法
Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator
摘要
Abstract
For near-field localization of multiple sound sources in reverberant environments, a algorithm model based on approximated kernel density estimator (KDE) was proposed. Multi-stage (MS) of sub-band processing was introduced to effectively solve the spatial aliasing by wide spacing. Spatial likelihood function (SLF) was built for multi-dimensional fusion by using two operators, sum (S) and prod (P). Then four algorithms, S-KDE, P-KDE, S-KDEMS, P-KDEMS, were derived. By the comprehensive comparison of the two statistical indicators root mean square error (RMSE) and percent-age of SLF (PSLF) which denoted the recognition, P-KDEMS is confirmed as a near-field localization algorithm of mul-tiple sound sources with high robustness and recognition.关键词
麦克风阵列/近似核密度估计/多阶段分频带处理/空域似然率函数/数据融合Key words
microphone array/approximated kernel density estimator/multi-stage of sub-band processing/spatial likeli-hood function/data fusion分类
信息技术与安全科学引用本文复制引用
房玉琢,许志勇,赵兆..基于近似核密度估计的近场多声源定位算法[J].通信学报,2017,38(1):106-116,11.基金项目
国家自然科学基金资助项目(No.61171167,No.61401203) （No.61171167,No.61401203）
江苏省自然科学基金资助项目(No.BK20130776) The National Natural Science Foundation of China (No.61171167, No.61401203), The Natural Science Founda-tion of Jiangsu Province (No.BK20130776) （No.BK20130776）
