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Localization of an Acoustic Fish-Tag using the Time-of-Arrival Measurements: Preliminary results using eXogenous Kalman Filter
Univ Porto, Fac Elect & Comp Engn, P-4200465 Porto, Portugal..
Univ Porto, Fac Elect & Comp Engn, P-4200465 Porto, Portugal..
Univ Porto, Fac Elect & Comp Engn, P-4200465 Porto, Portugal..
Norwegian Univ Sci & Technol, Dept Engn Cybernet, Ctr Autonomous Marine Operat & Syst, N-7491 Trondheim, Norway..
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2018 (English)In: 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Maciejewski, AA Okamura, A Bicchi, A Stachniss, C Song, DZ Lee, DH Chaumette, F Ding, H Li, JS Wen, J Roberts, J Masamune, K Chong, NY Amato, N Tsagwarakis, N Rocco, P Asfour, T Chung, WK Yasuyoshi, Y Sun, Y Maciekeski, T Althoefer, K AndradeCetto, J Chung, WK Demircan, E Dias, J Fraisse, P Gross, R Harada, H Hasegawa, Y Hayashibe, M Kiguchi, K Kim, K Kroeger, T Li, Y Ma, S Mochiyama, H Monje, CA Rekleitis, I Roberts, R Stulp, F Tsai, CHD Zollo, L, IEEE , 2018, p. 1695-1702Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the source localization problem of an acoustic fish-tag using the Time-of-Arrival measurement of an acoustic signal, transmitted by the fish-tag. The Time-of-Arrival measurements denote the pseudo-range information between the acoustic receiver and the fish-tag, except that the Time-of-Transmission of the acoustic signal is unknown. Starting with the pseudo-range measurement equation, a globally valid quasi-linear time-varying measurement model is presented that is independent of the Time-of-Transmission of the acoustic signal. Using this measurement model, an Uniformly Globally Asymptotically Stable (UGAS), three stage estimation strategy (eXogenous Kalman Filter) is designed to estimate the position of an acoustic fish-tag and evaluated against a benchmark Extended Kalman Filter based estimator. The efficacy of the developed estimation method is demonstrated experimentally, in presence of intermittent observations using an array of receivers mounted on three Unmanned Surface Vessels (USVs).

Place, publisher, year, edition, pages
IEEE , 2018. p. 1695-1702
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-246308DOI: 10.1109/IROS.2018.8593659ISI: 000458872701117ISBN: 978-1-5386-8094-0 (print)OAI: oai:DiVA.org:kth-246308DiVA, id: diva2:1297491
Conference
25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), OCT 01-05, 2018, Madrid, SPAIN
Note

QC 20190320

Available from: 2019-03-20 Created: 2019-03-20 Last updated: 2019-03-20Bibliographically approved

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Strandell Erstorp, EliasKuttenkeuler, Jacob

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