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Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Print: 0040-2508
ISSN Online: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v56.i4-5.100
15 pages

Imaging with Passive Sensing Systems Part 2: Sensor and Method Fusion

Yuriy V. Shkvarko
Visiting professor in the FIMEE, University of Guanajuato, Mexico
Rene Jaime-Rivas
Head of FIMEE at the University of Guanajuato, 36730 Salamanca, Gto. Mexico
Oscar G. Ibarra-Manzano
Guanajuato University, FIMEE, 36730, Salamanca, Gto, Mexico
Victor Ayala-Ramirez
Universidad de Guanajuato FIMEE, Tampico 912, Colonia Bellavista, Salamanca, Guanajuato, 36730 MEXICO
Jose A. Andrade-Lucio
Facultad de Ingenieria Mecánica, Eléctrica y Electrónica, Universidad de Guanajuato. A.P. 215-A, 36730. Salamanca, Gto., México

ABSTRACT

A combined experiment design and neural network-based approach to the problem of fusing the data of passive monitoring systems with different platforms of sensors is addressed. The two-stage imaging problem treatment is considered: (1) ED-based image formation; (2) image improvement/restoration via system or method fusion. Maximum entropy (ME) a priori image model is incorporated and two aggregation approaches, which incorporate model, measurements and calibration data, are developed. Computationally, the sensor and method fusion is implemented using the unified Hopfield maximum entropy neural network architecture. The results are illustrated by simulation examples.