• Y.Pavan Kumar Reddy
• Y.Sunanda
• N.Bala Dastagiri

Receiver localization indoors is the key element of Location Based Services (LBS) creation for wireless applications nowadays. Estimating the exact location is the key factor. Specific spatial estimation methods, such as Angle of Arrival, Time of Arrival have certain localization limitations. Indoor localization schemes based on received signal strength(RSS) may also be used to estimate receiver position. In this paper Neural Network based algorithms such as Nonlinear Autoregressive (NAR) and Nonlinear Autoregressive with External Input form (NARX) have been used to estimate the receiver's location in KLEF Library Block, Vaddeswaram, India. From our results it is clear that NARX performs better than NAR. For NARX the effective location rate is about 0.35 and the standard positional error deviation is also small.

Indoor Localization, GPS, RSS, MLNN, NAR, NARX

"Indoor localization Via Neural Networks and Wi-Fi Signal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 10, page no.687-692, October-2019, Available :http://www.jetir.org/papers/JETIR1912092.pdf

"Indoor localization Via Neural Networks and Wi-Fi Signal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 10, page no. pp687-692, October-2019, Available at : http://www.jetir.org/papers/JETIR1912092.pdf