Neural Networks for Fingerprinting-Based Indoor Localization Using Ultra-Wideband

AbstractThis paper discusses the use of neural networks in an underground radio-localization system. In a highly ag-gressive environment such as mines, reliability and robust-ness 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 pre-sented, providing a clear evidence of the role and impor-tance of the neural networks in offering good accuracy and precision to the final system. Index TermsIndoor localization, LOS, NLOS, fingerprint-ing-localization, ultra-wide-band (UWB), impulse response