Two-stage source tracking method using a multiple linear regression model in the expanded phase domain

• Published in: EURASIP journal on advances in signal processing Vol. 2012; no. 1; pp. 1 - 19
• Main Authors: Yang, Jae-Mo, Kang, Hong-Goo
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 10.01.2012; Springer Nature B.V; BioMed Central Ltd
• Subjects: Accuracy; Engineering; Estimators; Gaussian; Least squares method; Object Tracking and Monitoring Using Advanced Signal Processing Techniques; Phase distribution; Quantum Information Technology; Regression; Signal,Image and Speech Processing; Spintronics; Time delay; Tracking; inter-channel phase difference; time delay estimation; multiple linear regression; phase expansion; source tracking
• ISSN: 1687-6180; 1687-6172; 1687-6180
• DOI: 10.1186/1687-6180-2012-5

This article proposes an efficient two-channel time delay estimation method for tracking a moving speaker in noisy and re-verberant environment. Unlike conventional linear regression model-based methods, the proposed multiple linear regression model designed in the expanded phase domain shows high estimation accuracy in adverse condition because its the Gaussian assumption on phase distribution is valid. Therefore, the least-square-based time delay estimator using the proposed multiple linear regression model becomes an ideal estimator that does not require a complicated phase unwrapping process. In addition, the proposed method is extended to the two-stage recursive estimation approach, which can be used for a moving source tracking scenario. The performance of the proposed method is compared with that of conventional cross-correlation and linear regression-based methods in noisy and reverberant environment. Experimental results verify that the proposed algorithm significantly decreases estimation anomalies and improves the accuracy of time delay estimation. Finally, the tracking performance of the proposed method to both slow and fast moving speakers is confirmed in adverse environment.