Consiglio Nazionale delle Ricerche

Tipo di prodottoContributo in atti di convegno
TitoloParticle filters for rss-based localization in Wireless sensor networks: an experimental study
Anno di pubblicazione2006
Formato
  • Elettronico
  • Cartaceo
Autore/iC. Alippi, C. Morelli, M. Nicoli, V. Rampa, U. Spagnolini
Affiliazioni autoriDipartimento di Elettronica e Informazione, Politecnico di Milano; Istituto di Elettronica e d i Ingegneria dell'Informazione e delle Telecomunicazioni, CNR
Autori CNR e affiliazioni
  • VITTORIO RAMPA VQR
Lingua/e
  • inglese
AbstractThis paper focuses on the development of a radio localization technique for a wireless sensor network infrastructure where a large number of simple power-aware nodes are spread in indoor environments. Fixed and moving nodes exchange radio messages but can only measure mutual power figures such as the received signal strength (RSS) indicator. Local maximum likelihood estimation from propagation models suffers from false alarm problems due to incorrect position information, complex indoor propagation effects and simple hardware radio architectures. Here, we propose a Bayesian approach to estimate and track the position of a moving node from power maps obtained through field measurements. To lower the computational power required by grid-based algorithms, we exploit particle filter techniques that implement an irregular sampling of the a-posteriori probability space. Finally, experimental results are presented and discussed.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da957
Pagine a960
Pagine totali4
Rivista-
Numero volume della rivista-
Serie/CollanaProceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing
Attiva dal 1998
Editore: IEEE Service Center, - Piscataway, NJ
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1520-6149
Titolo chiave: Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing
Titolo proprio: Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing /
Titolo abbreviato: Proc. IEEE Int. Conf. Acoust. Speech Signal Process.
Titoli alternativi:
  • Proceedings
  • IEEE International Conference on Acoustics, Speech, and Signal Processing
  • Acoustics, Speech, and Signal Processing
Titolo del volumeProceedings of the 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing
Numero volume della serie/collana4
Curatore/i del volume-
ISBN1-4244-0469-X
DOI10.1109/ICASSP.2006.1661129
Editore
  • IEEE-Institute Of Electrical And Electronics Engineers Inc., Piscataway (Stati Uniti d'America)
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000245062900240)
  • Scopus (Codice:2-s2.0-33947631190)
Parole chiaveBayes methods, indoor radio, particle filtering (numerical methods), wireless sensor networks, maximum likelihood estimation
Link (URL, URI)http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=1661129&contentType=Conference+Publications&matchBoolean%3Dtrue%26searchField%3DSearch_All%26queryText%3D%28p_Authors%3ARampa+V%29
Titolo convegno/congresso2006 IEEE International Conference on Acoustics, Speech, and Signal Processing
Luogo convegno/congressoTolosa, France
Data/e convegno/congresso14-19/05/2006
RilevanzaInternazionale
RelazioneContributo
Titolo parallelo-
Note/Altre informazionihttp://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=3&SID=X2p3Df6@38c8JbacJ5L&page=1&doc=3 http://www.scopus.com/record/display.url?eid=2-s2.0-33947631190&origin=resultslist&sort=plf-f&src=s&st1=RAMPA+V&sid=CEbVWRiqwZVSP0GmE35DnhT%3a30&sot=b&sdt=b&sl=20&s=AUTHOR-NAME%28RAMPA+V%29&relpos=2&relpos=2&searchTerm=AUTHOR-NAME%28RAMPA%20V%29
Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
Moduli CNR
    Progetti Europei-
    Allegati
    • Articolo pubblicato
      Descrizione: Particle filters for rss-based localization in Wireless sensor networks: an experimental study

    Dati storici
    I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
    Area disciplinareInformation Technology & Communications Systems
    Area valutazione CIVRIngegneria industriale e informatica
    Descrizione sintetica del prodottoThis paper focuses on the development of a radio localization technique for a wireless sensor network infrastructure where a large number of simple power-aware nodes are spread in indoor environments. Fixed and moving nodes exchange radio messages but can only measure mutual power figures such as the received signal strength (RSS) indicator. Local maximum likelihood estimation from propagation models suffers from false alarm problems due to incorrect position information, complex indoor propagation effects and simple hardware radio architectures. Here, we propose a Bayesian approach to estimate and track the position of a moving node from power maps obtained through field measurements. To lower the computational power required by grid-based algorithms, we exploit particle filter techniques that implement an irregular sampling of the a-posteriori probability space. Finally, experimental results are presented and discussed