Tree-Based Recursive Expectation-Maximization Algorithm for Localization of Acoustic Sources

• Published in: IEEE/ACM transactions on audio, speech, and language processing Vol. 23; no. 10; pp. 1692 - 1703
• Main Authors: Dorfan, Yuval, Gannot, Sharon
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Algorithms; Bi-directional tree topologies; Bidirectional control; distributed signal processing; Estimation; Microphones; recursive expectation-maximization (REM); Signal processing algorithms; speaker localization; Speech; Time-frequency analysis; wireless acoustic sensor networks (WASNs)
• ISSN: 2329-9290; 2329-9304
• DOI: 10.1109/TASLP.2015.2444654

The problem of distributed localization for ad hoc wireless acoustic sensor networks (WASNs) is addressed in this paper. WASNs are characterized by low computational resources in each node and by limited connectivity between the nodes. Novel bi-directional tree-based distributed estimation-maximization (DEM) algorithms are proposed to circumvent these inherent limitations. We show that the proposed algorithms are capable of localizing static acoustic sources in reverberant enclosures without a priori information on the number of sources. Unlike serial estimation procedures (like ring-based algorithms), the new algorithms enable simultaneous computations in the nodes and exhibit greater robustness to communication failures. Specifically, the recursive distributed EM (RDEM) variant is better suited to online applications due to its recursive nature. Furthermore, the RDEM outperforms the other proposed variants in terms of convergence speed and simplicity. Performance is demonstrated by an extensive experimental study consisting of both simulated and actual environments.