Acoustic Sensor Self-Localization: Models and Recent Results. (22nd October 2017)

• Record Type: Journal Article
• Authors: Haddad, Diego B.; Lima, Markus V. S.; Martins, Wallace A.; Biscainho, Luiz W. P.; Nunes, Leonardo O.; Lee, Bowon
• Other Names: Mitton Nathalie Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2017(2017)
• Publication Date: 2017-10-22
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2017/7972146
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : The wide availability of mobile devices with embedded microphones opens up opportunities for new applications based on acoustic sensor localization (ASL). Among them, this paper highlights mobile device self-localization relying exclusively on acoustic signals, but with previous knowledge of reference signals and source positions. The problem of finding the sensor position is stated as a function of estimated times-of-flight (TOFs) or time-differences-of-flight (TDOFs) from the sound sources to the target microphone, and the main practical issues involved in TOF estimation are discussed. Least-squares ASL solutions are introduced, followed by other strategies inspired by sound source localization solutions: steered-response power, which improves localization accuracy, and a new region-based search, which alleviates complexity. A set of complementary techniques for further improvement of TOF/TDOF estimates are reviewed: sliding windows, matching pursuit, and TOF selection. The paper proceeds with proposing a novel ASL method that combines most of the previous material, whose performance is assessed in a real-world example: in a typical lecture room, the method achieves accuracy better than 20 cm.