Localization of an Acoustic Fish-Tag using the Time-of-Arrival Measurements: Preliminary results using eXogenous Kalman Filter

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

R. Praveen Jain (Author) Other; A. Pedro Aguiar (Author) FEUP; João Borges de Sousa (Author) FEUP; Artur Zolich (Author) Other; Tor Arne Johansen (Author) Other; Jo Arve Alfredsen (Author) Other; Elias Erstorp (Author) Other; Jakob Kuttenkeuler (Author) Other

Conference proceedings International

Title: IEEE International Conference on Intelligent Robots and Systems

Pages: 1695-1702

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018

1 October 2018 through 5 October 2018

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

INSPEC

Other information

Authenticus ID: P-00Q-94R

DOI: 10.1109/iros.2018.8593659

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).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8