A robust vector matching localization approach based on multiple channels SSD fingerprinting of ZigBee Networks

Abstract

We present a robust multiple-channel vector-matching localization approach (MCVM) based on signal strength difference (SSD) fingerprinting of ZigBee Network. Compared with some existing algorithms, our presented approach has threefold advantages: firstly, far fewer numbers of received signal strength(RSS) measurements and reference nodes are needed; secondly, it shows more robustness to the fluctuation of RSS; thirdly, it requires low time-consuming signal strength collection surveys in the location space. We demonstrate the performances of our algorithm experimentally using different numbers of channels, reference nodes and training points. The Cramer-Rao Low Bound(CRLB) of SSD is derived in order to compare the performance of the different localization methods addressed. The experiment results show the efficacy of our proposed approach.