The localization and tracking of human targets are cast as linear inverse obstacle problems and solved by means of the factorization method. The proposed approach is validated against indoor monitoring and multifrequency sensing, where Green's function pertaining to the involved realistic scenarios has been determined through full-wave simulations. The results, which include the analysis of the impact on final performance of the number of employed transceivers as well as preliminary 2-D processing of realistic data simulated in 3-D geometry, show good robustness to noise and model errors.

Noncooperative Localization and Tracking through the Factorization Method

R. Palmeri;M. T. Bevacqua
;
A. F. Morabito;Isernia T
2019

Abstract

The localization and tracking of human targets are cast as linear inverse obstacle problems and solved by means of the factorization method. The proposed approach is validated against indoor monitoring and multifrequency sensing, where Green's function pertaining to the involved realistic scenarios has been determined through full-wave simulations. The results, which include the analysis of the impact on final performance of the number of employed transceivers as well as preliminary 2-D processing of realistic data simulated in 3-D geometry, show good robustness to noise and model errors.
Microwave imaging, wireless sensor networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/713
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