Extended Vector-Based EB-ESPRIT Method

• Published in: IEEE/ACM transactions on audio, speech, and language processing Vol. 28; pp. 1692 - 1705
• Main Authors: Jo, Byeongho, Zotter, Franz, Choi, Jung-Woo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Audio data; Computer simulation; Covariance matrices; Direction-of-arrival estimation; EB-ESPRIT; Estimation; Harmonic analysis; Microphone arrays; Monte Carlo simulation; Parameter estimation; recurrence relations; Sound fields; Sound sources; Speech processing; Spherical harmonics
• ISSN: 2329-9290; 2329-9304
• DOI: 10.1109/TASLP.2020.2996090

The estimation of direction of arrivals (DoAs) from spherical microphone array data is one of the key issues in extracting source information from all-around audio recordings. One such technique is the eigenbeam estimation of signal parameters via the rotational invariance technique (EB-ESPRIT), which separates the signal subspace related to the stationary sound field and then directly estimates DoAs of multiple sound sources. EB-ESPRIT has been evolved in many different ways by involving different types of recurrence relations of spherical harmonics, all of which are able to identify DoAs of a limited number of sources that are noticeably smaller than the number of finite-order spherical harmonic coefficients recorded. In this work, we report that it is possible to go beyond the known limits of detectable sources. The proposed formula is also based on conventional recurrence relations and probably permits to reach the ultimate limit by additional constraints of the signal parameters that can better exploit the highest-order coefficients. Monte-Carlo simulations conducted with various source positions and signal-to-noise ratios (SNRs) reveal that the proposed technique can detect more sources with insignificant loss in estimation performance and robustness.