A 3D Fingerprinting Positioning Method Based on Cellular Networks

Abstract

A new 3D fingerprinting positioning scheme based on cellular networks is proposed by using implicit information of the location around geographic environments. Compared with original fingerprint positioning scheme, singular measurement is processed at the beginning of the proposed scheme. The main improvement of our proposed scheme is to employ cell matching degree and choose the best reasonable fingerprint according to the correlation of its surrounding points. Additionally, in order to improve searching efficiency, a new searching window is introduced. Finally, compared with the maximum likelihood method and the weighted K nearest neighbors method, the promising numerical results are also presented.