DoA Estimation of Room Reflections Using NN-Based MUSIC Algorithm

Haowen Li, Wen Zhang, Lijun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The estimation of direction of arrival (DoA) for coherent sound sources, such as direct sound and early reflections in a room environment, is crucial. However, most traditional algorithms, like the multiple signal classification (MUSIC) algorithm, require observed signals to be non-coherent and can only be applied to narrowband signals. To tackle this issue, this paper introduces a neural network (NN)-based broadband MUSIC algorithm. By substituting the covariance matrix in the MUSIC algorithm with a pseudo-covariance matrix estimated through the network, this method can overcome the limitation of locating coherent broadband sources. Simulation results have shown that this proposed approach can accurately estimate the DoAs of direct sound and first-order reflections in both noisy and reverberant environments.

Original languageEnglish
Title of host publication2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1960-1965
Number of pages6
ISBN (Electronic)9798350300673
DOIs
StatePublished - 2023
Event2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023 - Taipei, Taiwan, Province of China
Duration: 31 Oct 20233 Nov 2023

Publication series

Name2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023

Conference

Conference2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period31/10/233/11/23

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