Comparative Analysis of Local Positioning Methods in Wi-Fi/Indoor Networks

Abstract

The rapid development of various LBS-oriented applications and services requires the development of new and improvement of known local positioning methods in order to increase the accuracy of determining the user's coordinates. First of all, it connects to methods for determining the location of users in rooms, subject to a high concentration of users and the presence of various difficulties in the propagation of radio signals. To determine the local location of a user in a Wi-Fi/Indoor network, the Fingerprinting method is considered. The comparison of the results of user positioning in the Wi-Fi/Indoor network based on the Fingerprinting method using various algorithms for determining user coordinates, such as the probabilistic Bayesian method and complex approximation using complex planar quadratic splines, was carried out. It has been established that the use of the Fingerprinting local positioning method using quadratic complex flat splines can improve the accuracy of determining the user's location coordinates, thereby ensuring the provision of LBS services and applications to users in the premises.