JOURNAL OF COMMUNICATIONS (JCM)
ISSN : 1796-2021
Volume : 4 Issue : 4 Date : May 2009
Neural Networks for Fingerprinting-Based Indoor Localization Using Ultra-Wideband
Anthony Taok, Nahi Kandil, and Sofiene Affes
Full Text: PDF (1,807 KB)
This paper discusses the use of neural networks in an underground radio-localization system. In a
highly aggressive environment such as mines, reliability and robustness are essential to any
operational system. Using UWB as the physical wireless propagation medium and combined with
fingerprinting-geolocation and neural networks, this work tends to overcome many of the problems
encountered in indoor environments. Full description of the system and the adopted approach will
help accentuate the role of neural networks in improving the overall performance. Moreover a
comparison between MLP and RBF performance is presented, providing a clear evidence of the role
and importance of the neural networks in offering good accuracy and precision to the final system.
Indoor localization, LOS, NLOS, fingerprinting-localization, ultra-wide-band (UWB), impulse
response (IR), neural networks (NN), multi-layer perceptron (MLP), radial basis functions (RBF).