dc.contributor.author | jain, praveen | |
dc.contributor.author | Zolich, Artur Piotr | |
dc.contributor.author | Erstorp, E | |
dc.contributor.author | Johansen, Tor Arne | |
dc.contributor.author | Alfredsen, Jo Arve | |
dc.contributor.author | Aguiar, A Pedro | |
dc.contributor.author | Kuttenkeuler, J | |
dc.contributor.author | Sousa, João Borges de | |
dc.date.accessioned | 2019-04-29T11:04:32Z | |
dc.date.available | 2019-04-29T11:04:32Z | |
dc.date.created | 2018-12-26T17:16:38Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2153-0858 | |
dc.identifier.uri | http://hdl.handle.net/11250/2595930 | |
dc.description.abstract | 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). | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.title | Localization of an Acoustic Fish-Tag using the Time-of-Arrival Measurements: Preliminary results using eXogenous Kalman Filter | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.journal | IEEE International Conference on Intelligent Robots and Systems. Proceedings | nb_NO |
dc.identifier.doi | 10.1109/IROS.2018.8593659 | |
dc.identifier.cristin | 1647204 | |
dc.relation.project | Norges forskningsråd: 223254 | nb_NO |
dc.relation.project | EC/H2020/642153 | nb_NO |
dc.description.localcode | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,63,25,0 | |
cristin.unitname | Institutt for teknisk kybernetikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |