Paper Info
Title
A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization.
Abstract
The traditional weighted MUSIC algorithm is usually implemented based on a sparsity assumption named W-Disjoint Orthogonality (WDO) when the number of sound sources is unknown, which may not be suitable in many scenarios. In this paper, a modified weighted MUSIC algorithm is proposed to improve the localization performance in multiple sound sources. Instead of using the maximum eigenvalue as the weight of each frequency band, we use the signal-to-noise ratio (SNR) as the weight coefficient of each frequency band, which can reduce the disturbance cases by the multiple sources bands. The simulation experiments are conducted to evaluate the performance of our proposed method and compare with the traditional weighted MUSIC algorithm. The results show that the proposed algorithms have a better localization accuracy in multiple-source environment.
Year
DOI
Venue
2018
10.1109/ICDSP.2018.8631636
DSL
Keywords
Field
DocType
Multiple signal classification,Microphone arrays,Signal processing algorithms,Eigenvalues and eigenfunctions,Covariance matrices,Music
Multiple signal classification,Pattern recognition,Computer science,Frequency band,Orthogonality,Weight coefficient,Artificial intelligence,Maximum eigenvalue,Signal processing algorithms
Conference
ISSN
ISBN
Citations 
1546-1874
978-1-5386-6811-5
2
PageRank 
References 
Authors
0.37
0
5
Name
Order
Citations
PageRank
Shan Gao1136.31
Yankun Huang220.37
Tao Zhang322069.03
Xihong Wu427953.02
Tianshu Qu5245.50