Fingerprint positioning method in inter-coordinate estimation using weighted average of existence probability distribution output of 3-layer NN

Abstract

This contribution describes a fingerprint position estimation using RSSI (Received Signal Strength Indicator) of wireless LAN Access Points (APs) that employs Neural Network (NN). We propose position estimation using the weighted intermediate point to estimate the exact position. In this method, RSSI of UD (User Data) is collated with the RSSI in DB (data base). RSSI of DB was measured on coordinates in advance. Therefore, one of the coordinates is selected as the estimation result. The coordinate closest to correct point is selected in case of estimation at the intermediate point of the coordinates. In this study, we propose to estimate the intermediate point using weighting with the existence probability distribution of limited coordinate output from NN. The accuracy of proposed position estimation method was verified using three-layer NN based on measured data.