Iterative and Complex Orthogonal Matching Pursuit for Broadband Sparse Sound Field Reconstruction

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Xu, Shaoheng
Zhang, Jihui Aimee
Abhayapala, Thushara
Bastine, Amy
Samarasinghe, Prasanga

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Institute of Electrical and Electronics Engineers Inc.

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Virtual navigation through a large listening region of interest (ROI) has broad applications. Obtaining this from limited recordings in reverberant environments for broadband source distributions poses many challenges. In this paper, we address this problem by proposing an efficient method for sparse sound field representation and reconstruction. Our method uses the Iterative Group Complex Orthogonal Matching Pursuit (IG-COMP) as a novel approach to iteratively and sparsely decompose the recorded sound field into a selected set of virtual sources (ViSrcs) and reconstruct it over the ROI. IG-COMP builds upon the Complex Orthogonal Matching Pursuit (COMP) to address broadband sources. It iteratively refines the virtual source selection while ensuring reduced computational complexity. We demonstrate the effectiveness of IG-COMP through simulations of several broadband sources distributed in a reverberant room. These simulations showcase the method's ability to achieve high-fidelity sound field reproduction across a large ROI using a compact equivalent representation.

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2024 18th International Workshop on Acoustic Signal Enhancement, IWAENC 2024 - Proceedings

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