Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloHidden Markov Model for multidimensional wavefront tracking
Anno di pubblicazione2002
Formato
  • Elettronico
  • Cartaceo
Autore/iV. Rampa, U. Spagnolini, M. Nicoli
Affiliazioni autori1 IEIIT-MI CNR 2 e 3 Dipartimento di Elettronica e Informazione - Politecnico di Milano
Autori CNR e affiliazioni
  • VITTORIO RAMPA
Lingua/e
  • inglese
AbstractIn subsurface sensing, the estimation of the delays (wavefronts) of the backscattered wavefields is a very time-consuming, mostly manual task. We propose delay estimation by exploiting the continuity of the wavefronts modeled as a Markov chain. Each wavefront is a realization of Brownian motion with a correlation that depends on the distance between each source/receiver pair. Therefore, the delay profiles can be tracked with any known method by assuming that the ordered sequence of signals is described by a hidden Markov model (HMM). Linear array provides the most natural data-ordering, and in this case the tracking algorithms can preserve the target/tracker association. However, when measurements are multidimensional, the volume-slicing strategies, that are able to get a linear array of (virtually) ordered signals, select the measurements independently of the target. When different estimates along slices are merged mis-ties can occur easily. Since data-ordering is a main issue for irregularly positioned sources and receivers, we propose a region growing tracking technique that orders (for each specified target) the data while tracking. The ordering is based on the maximum a posteriori probability of detection. Experiments based on multidimensional measurements show that this region growing tracking algorithm based on HMM preserves the target/tracker association.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da651
Pagine a662
Pagine totali12
RivistaIEEE transactions on geoscience and remote sensing
Attiva dal 1980
Editore: Institute of Electrical and Electronics Engineers, - New York, N.Y.
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 0196-2892
Titolo chiave: IEEE transactions on geoscience and remote sensing
Titolo proprio: IEEE transactions on geoscience and remote sensing
Titolo abbreviato: IEEE trans. geosci. remote sens.
Titoli alternativi:
  • Institute of Electrical and Electronics Engineers transactions on geoscience and remote sensing
  • I.E.E.E. transactions on geoscience and remote sensing
  • Transactions on geoscience and remote sensing
Numero volume della rivista40
Fascicolo della rivista3
DOI10.1109/TGRS.2002.1000324
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000175552900012)
  • IEEE Xplore digital library (Codice:1000324)
Parole chiaveArray processing, delay estimation, Viterbi algorithm, horizon picking, target tracking
Link (URL, URI)http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=1000324
Titolo parallelo-
Data di accettazione-
Note/Altre informazionihttp://ieeexplore.ieee.org/search/srchabstract.jsp?arnumber=1000324&isnumber=21604&punumber=36&k2dockey=1000324@ieeejrns&query=((rampa)%3Cin%3Eau+)&pos=2&access=no
Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
Moduli CNR
  • ICT.P07.005.001 : Reti wireless integrate per accesso ad alta velocita'
Progetti Europei-
Allegati
Hidden Markov Model for multidimensional wavefront tracking (documento privato )
Descrizione: Hidden Markov Model for multidimensional wavefront tracking
Tipo documento: application/x-pdf

Dati associati a vecchie tipologie
I dati associati a vecchie tipologie non sono modificabili, derivano dal cambiamento della tipologia di prodotto e hanno solo valore storico.
Editore
  • IEEE - Institute of Electrical and Electronics Engineers, Piscataway, N.J. (Stati Uniti d'America)

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
Rivista ISIIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING [03091J0]
Descrizione sintetica del prodottoIn subsurface sensing, the estimation of the delays (wavefronts) of the backscattered wavefields is a very time-consuming, mostly manual task. We propose delay estimation by exploiting the continuity of the wavefronts modeled as a Markov chain. Each wavefront is a realization of Brownian motion with a correlation that depends on the distance between each source/receiver pair. Therefore, the delay profiles can be tracked with any known method by assuming that the ordered sequence of signals is described by a hidden Markov model (HMM). Linear array provides the most natural data-ordering, and in this case the tracking algorithms can preserve the target/tracker association. However, when measurements are multidimensional, the volume-slicing strategies, that are able to get a linear array of (virtually) ordered signals, select the measurements independently of the target. When different estimates along slices are merged mis-ties can occur easily. Since data-ordering is a main issue for irregularly positioned sources and receivers, we propose a region growing tracking technique that orders (for each specified target) the data while tracking. The ordering is based on the maximum a posteriori probability of detection. Experiments based on multidimensional measurements show that this region growing tracking algorithm based onHMMpreserves the target/tracker association.