Open AccessApplication of artificial neural networks for fusion of data from radar and depth sensors applied for persons’ monitoring
Author(s) -
Paweł Mazurek
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1379/1/012051
Subject(s) - sensor fusion , artificial neural network , radar , artificial intelligence , computer science , fusion , computer vision , position (finance) , impulse (physics) , telecommunications , finance , quantum mechanics , economics , philosophy , linguistics , physics
The research reported in this paper is related to the fusion of measurement data from the impulse-radar sensors and infrared depth sensors applied in a system for unobtrusive monitoring of elderly persons. Three methods for data fusion, based on the artificial neural networks – one trained on real-world data, and two trained on synthetic data generated on the basis of two different models of the data – are compared with respect to their capacity of decreasing the uncertainty of position estimation in a series of experiments which involved the tracking of a moving person.