Efficient Implementation of GMDA-based DOA Technique Using Pre-training Phase Unwrapping for Source Localization

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초록

In this paper, a novel technique that improves the performance of generalized mixture decomposition algorithm (GMDA) based on pre-training phase unwrapping. From the investigation of the GMDA scheme, it was discovered that the conventional GMDA technique cannot fully consider phase unwrapping, because the estimated inter-channel phase difference (IPD) slope is initialized randomly. To avoid this phenomenon, the proposed GMDA approach initialized the IPD slope from the data of low-frequency bins. Experimental results show that comparing to the conventional GMDA technique, the proposed GMDA technique based on pre-training phase unwrapping obtains a lower estimation error. When integrated into a source localization system, the result of source localization is improved.

키워드

Source localizationInter-channel phase differenceGeneralized mixture decomposition algorithmPre-trainingTIME-DELAY ESTIMATIONEIGENVALUE DECOMPOSITION ALGORITHMMAXIMUM-LIKELIHOOD
제목
Efficient Implementation of GMDA-based DOA Technique Using Pre-training Phase Unwrapping for Source Localization
저자
Kang, Sang-IckKim, SeongbinLee, Sangmin
DOI
10.3966/160792642020052103021
발행일
2020
유형
Article
저널명
Journal of Internet Technology
21
3
페이지
841 ~ 847