Acoustic Indoor Localization Augmentation by Self-Calibration and Machine Learning

Acoustic Indoor Localization Augmentation by Self-Calibration and Machine Learning

An acoustic transmitter can be located by having multiple static microphones. These microphones are synchronized and measure the time differences of arrival (TDoA). Usually, the positions of the microphones are assumed to be known in advance. However, in practice, this means they have to be manually...

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Bibliographic Details
Main Authors: Joan Bordoy, Dominik Jan Schott, Jizhou Xie, Amir Bannoura, Philip Klein, Ludwig Striet, Fabian Hoeflinger, Ivo Haering, Leonhard Reindl, Christian Schindelhauer
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sensors
Subjects:
self-calibration
localization
ultrasound
machine learning
indoor localization
tdoa
random forest
Online Access:https://www.mdpi.com/1424-8220/20/4/1177

Internet

https://www.mdpi.com/1424-8220/20/4/1177

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