Indoor cooperative positioning based on fingerprinting and support vector machines

Abstract

For location in indoor environments, the fingerprinting technique seems the most attractive one. It gives higher localization accuracy than the parametric technique because of the existence of multipath propagation and fast fading phenomena that are difficult to model. This paper introduces a novel positioning system based on wireless the IEEE802.15.4/ZigBee standard and employs Support Vector Machines (SVMs). The system is cost-effective since it works with real deployed IEEE 802.15.4/ZigBeeTM sensors nodes. The whole system requires minimal setup time, which makes it readily available for real-world applications. The resulting algorithm demonstrates a superior performance compared to the conventional algorithms. © 2012 Springer-Verlag Berlin Heidelberg.