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Passive target detection and tracking from electromagnetic field measurements
Author(s) -
Gao Lin,
Selleri Stefano,
Battistelli Giorgio,
Chisci Luigi,
Pelosi Giuseppe
Publication year - 2020
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.22321
Subject(s) - tracking (education) , particle filter , computer science , electromagnetic field , artificial neural network , electromagnetic environment , field (mathematics) , filter (signal processing) , bernoulli's principle , time domain , set (abstract data type) , real time computing , artificial intelligence , acoustics , computer vision , engineering , physics , mathematics , aerospace engineering , telecommunications , programming language , psychology , pedagogy , quantum mechanics , pure mathematics
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.

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