An Improved Wi-Fi Indoor Positioning Method via Signal Strength Order Invariance

It is well known that Wi-Fi indoor positioning accuracy is vulnerable to environmental fluctuations. In this paper, we propose a novel Wi-Fi indoor positioning method which applies signal strength order invariance (SSOI) to overcome the problem of environment influence and hence improve the positioning accuracy. In the off-line phase we save not only the signal strength of reference points but also the corresponding signal strength order. Then in the online phase, the measured signal strength and the associated order are used jointly to estimate the unknown point's coordinate. Simulation and experimental results both demonstrate that our proposed algorithm can achieve better positioning accuracy than the methods using the traditional nearest neighbor (NN) or K-nearest-neighbors (KNN) fingerprinting algorithm only.