Complex spline approximation in positioning problems
The rapid development of various applications and services that use the user’s current LBS location and crowdsourcing require constant improvement of positioning methods in order to improve location accuracy. The problems of local positioning of users indoors in conditions of high concentration of users and the presence of difficulties in the propagation of radio signals deserve special attention. Comparative analysis of known IPS local positioning methods proves the advantage of using the fingerprinting method according to the criterion of positioning accuracy. It is proposed a method of user positioning in a Wi-Fi/Indoor network, which is based on the fingerprinting method and complex spline approximation. We carry out a comparison of the results of positioning in the Wi-Fi/Indoor network based on the fingerprinting method using different methods of user location determination, such as the k-nearest neighbors k-NN method, the weighted k-nearest neighbors k-WNN method and the complex spline approximation based on the quadratic planar spline. It is shown that application of complex spline approximation provides an increase in the accuracy of user positioning in the Wi-Fi/Indoor network, thereby making it possible to provide LBS-oriented services to users indoors.
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