Acoustic Sensor Self-Localization: Models and Recent Results
| Autor: | Leonardo O. Nunes, Bowon Lee, Diego B. Haddad, Markus V. S. Lima, Luiz W. P. Biscainho, Wallace A. Martins |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Computer Networks and Communications
Computer science Microphone business.industry lcsh:T Speech recognition 020206 networking & telecommunications 02 engineering and technology Function (mathematics) Acoustic source localization lcsh:Technology Power (physics) lcsh:Telecommunication Set (abstract data type) 030507 speech-language pathology & audiology 03 medical and health sciences Position (vector) lcsh:TK5101-6720 0202 electrical engineering electronic engineering information engineering Computer vision Artificial intelligence Electrical and Electronic Engineering 0305 other medical science business Information Systems |
| Zdroj: | Wireless Communications and Mobile Computing, Vol 2017 (2017) |
| ISSN: | 1530-8677 1530-8669 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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