This paper presents a novel approach to the localization of moving targets in a complex environment based on the measurement of the perturbations induced by the target presence on an independently-generated time-varying electromagnetic field. Field perturbations are measured via a set of sensors deployed over the domain of interest and used to detect and track a possible target by resorting to a particle Bernoulli filter (PBF). To comply with real-time operation, the PBF works along with an artificial neural network (ANN) model of the environment trained offline via finite elements (FEs). The performance of the proposed algorithm is assessed via simulation experiments.

Passive target detection and tracking from electromagnetic field measurements / Gao L.; Selleri S.; Battistelli G.; Chisci L.; Pelosi G.. - In: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING. - ISSN 1096-4290. - STAMPA. - (2020), pp. 0-0. [10.1002/mmce.22321]

Passive target detection and tracking from electromagnetic field measurements

Gao L.;Selleri S.
;
Battistelli G.;Chisci L.;Pelosi G.
2020

Abstract

This paper presents a novel approach to the localization of moving targets in a complex environment based on the measurement of the perturbations induced by the target presence on an independently-generated time-varying electromagnetic field. Field perturbations are measured via a set of sensors deployed over the domain of interest and used to detect and track a possible target by resorting to a particle Bernoulli filter (PBF). To comply with real-time operation, the PBF works along with an artificial neural network (ANN) model of the environment trained offline via finite elements (FEs). The performance of the proposed algorithm is assessed via simulation experiments.
2020
0
0
Goal 9: Industry, Innovation, and Infrastructure
Gao L.; Selleri S.; Battistelli G.; Chisci L.; Pelosi G.
File in questo prodotto:
File Dimensione Formato  
IJRFMCAE 2020 Gao - preprint.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 2.81 MB
Formato Adobe PDF
2.81 MB 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/2158/1200323
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact