Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator - Yu-zhuo FANG; Zhi-yong XU; Zhao ZHAO (Tongxin xuebao)
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 percentage of SLF (PSLF) which denoted the recognition,P-KDEMS is confirmed as a near-field localization algorithm of multiple sound sources with high robustness and recognition.