{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:44:43Z","timestamp":1760237083118,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,20]],"date-time":"2020-02-20T00:00:00Z","timestamp":1582156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["FKZ 01IS18011C"],"award-info":[{"award-number":["FKZ 01IS18011C"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 measured, which is a cumbersome job and is prone to errors. In this paper, we present two novel approaches which do not require manual measurement of the receiver positions. The first method uses an inertial measurement unit (IMU), in addition to the acoustic transmitter, to estimate the positions of the receivers. By using an IMU as an additional source of information, the non-convex optimizers are less likely to fall into local minima. Consequently, the success rate is increased and measurements with large errors have less influence on the final estimation. The second method we present in this paper consists of using machine learning to learn the TDoA signatures of certain regions of the localization area. By doing this, the target can be located without knowing where the microphones are and whether the received signals are in line-of-sight or not. We use an artificial neural network and random forest classification for this purpose.<\/jats:p>","DOI":"10.3390\/s20041177","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T10:49:16Z","timestamp":1582282156000},"page":"1177","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Acoustic Indoor Localization Augmentation by Self-Calibration and Machine Learning"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3575-6513","authenticated-orcid":false,"given":"Joan","family":"Bordoy","sequence":"first","affiliation":[{"name":"Department of Computer Science (IIF), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0869-4604","authenticated-orcid":false,"given":"Dominik Jan","family":"Schott","sequence":"additional","affiliation":[{"name":"Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jizhou","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Computer Science (IIF), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3969-7725","authenticated-orcid":false,"given":"Amir","family":"Bannoura","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Bethlehem University, P.O. Box 11407, Bethlehem, 92248 Jerusalem, Palestine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip","family":"Klein","sequence":"additional","affiliation":[{"name":"Department of Computer Science (IIF), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ludwig","family":"Striet","sequence":"additional","affiliation":[{"name":"Department of Computer Science (IIF), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0609-172X","authenticated-orcid":false,"given":"Fabian","family":"Hoeflinger","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Highspeed Dynamics, Ernst-Mach-Institute (EMI), 79104 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0318-6133","authenticated-orcid":false,"given":"Ivo","family":"Haering","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Highspeed Dynamics, Ernst-Mach-Institute (EMI), 79104 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-8929","authenticated-orcid":false,"given":"Leonhard","family":"Reindl","sequence":"additional","affiliation":[{"name":"Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8320-8581","authenticated-orcid":false,"given":"Christian","family":"Schindelhauer","sequence":"additional","affiliation":[{"name":"Department of Computer Science (IIF), University of Freiburg, 79110 Freiburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TSMCC.2007.905750","article-title":"Survey of wireless indoor positioning techniques and systems","volume":"37","author":"Liu","year":"2007","journal-title":"IEEE Trans. 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