TY - JOUR A2 - Mitton, Nathalie AU - Haddad, Diego B. AU - Lima, Markus V. S. AU - Martins, Wallace A. AU - Biscainho, Luiz W. P. AU - Nunes, Leonardo O. AU - Lee, Bowon PY - 2017 DA - 2017/10/22 TI - Acoustic Sensor Self-Localization: Models and Recent Results SP - 7972146 VL - 2017 AB - 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. SN - 1530-8669 UR - https://doi.org/10.1155/2017/7972146 DO - 10.1155/2017/7972146 JF - Wireless Communications and Mobile Computing PB - Hindawi KW - ER -