Performance of Improved Fuzzy Indoor Zone Positioning Systems in Wireless Sensor Networks

Abstract

This paper proposes a zone-based indoor positioning scheme using a wireless sensor networks (WSNs) in conjunction with a fuzzy-based algorithm. We propose using the received signal strength indicator (RSSI) to determine the distance between the target node and reference nodes in indoor environments. This propagation characteristic has previously been used to construct a signal propagation channel model. We divide the RSSI into several power levels based on the rate of signal attenuation over distance, and the indoor environment is splitting up into zones. A fuzzy inference system (FIS) algorithm is used to improve the accuracy of localization. The RSSI values from several reference nodes are used as inputs in the FIS to estimate the location of the target node within the zone. Simulation results show that the fuzzy rectangular splitting method is the most suitable approach to splitting up the zone.