Autonomous underwater navigation remains, as of today, a challenging task. The marine environment limits the number of sensors available for precise localization, hence Au- tonomous Underwater Vehicles (AUVs) usually rely on inertial and velocity sensors to obtain an estimate of their position either through dead reckoning or by means of more sophisticated navigation lters (such as Kalman lters and its extensions). On the other hand, acoustic localization makes possible the determination of a reliable vehicles pose estimate exploiting suitable acoustic modems; such estimate can even be integrated within the navigation filter of the vehicle in order to increase its accuracy. In this paper, the authors discuss the development and the performance of an Ultra-Short BaseLine (USBL)-aided buoy to improve the localization of underwater vehicles. At rst, the components and the physical realization of the buoy will be discussed; then, the procedure to compute the position of the target will be analyzed. The following part of the paper will be focused on the development of a recursive state estimation algorithm to process the measurements computed by the buoy; specifically, Extended Kalman Filter has been adopted to deal with the nonlinearities of the sensors housed on the buoy. A validation of the measurement filtering through experimental tests is also proposed.

An IMU and USBL-aided buoy for underwater localization / Allotta, Benedetto; Bianchi, Matteo; Fanelli, Francesco; Gelli, Jonathan; Monni, Niccolò; Pagliai, Marco; Palma, Nicola; Ridolfi, Alessandro. - ELETTRONICO. - (2017), pp. 0-0. (Intervento presentato al convegno VII International Conference on Computational Methods in Marine Engineering (MARINE 2017) tenutosi a Nantes, France nel 15-17 May 2017).

An IMU and USBL-aided buoy for underwater localization

ALLOTTA, BENEDETTO;BIANCHI, MATTEO;FANELLI, FRANCESCO;GELLI, JONATHAN;PAGLIAI, MARCO;RIDOLFI, ALESSANDRO
2017

Abstract

Autonomous underwater navigation remains, as of today, a challenging task. The marine environment limits the number of sensors available for precise localization, hence Au- tonomous Underwater Vehicles (AUVs) usually rely on inertial and velocity sensors to obtain an estimate of their position either through dead reckoning or by means of more sophisticated navigation lters (such as Kalman lters and its extensions). On the other hand, acoustic localization makes possible the determination of a reliable vehicles pose estimate exploiting suitable acoustic modems; such estimate can even be integrated within the navigation filter of the vehicle in order to increase its accuracy. In this paper, the authors discuss the development and the performance of an Ultra-Short BaseLine (USBL)-aided buoy to improve the localization of underwater vehicles. At rst, the components and the physical realization of the buoy will be discussed; then, the procedure to compute the position of the target will be analyzed. The following part of the paper will be focused on the development of a recursive state estimation algorithm to process the measurements computed by the buoy; specifically, Extended Kalman Filter has been adopted to deal with the nonlinearities of the sensors housed on the buoy. A validation of the measurement filtering through experimental tests is also proposed.
2017
Proceedings of VII International Conference on Computational Methods in Marine Engineering (MARINE 2017)
VII International Conference on Computational Methods in Marine Engineering (MARINE 2017)
Nantes, France
15-17 May 2017
Allotta, Benedetto; Bianchi, Matteo; Fanelli, Francesco; Gelli, Jonathan; Monni, Niccolò; Pagliai, Marco; Palma, Nicola; Ridolfi, Alessandro
File in questo prodotto:
File Dimensione Formato  
MARINE2017_UNIFI_DEF_compr.pdf

Accesso chiuso

Descrizione: Articolo principale
Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 509.58 kB
Formato Adobe PDF
509.58 kB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1084955
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact