A novel method for measurement points selection in access points localization

Abstract

Precise localization of access points (APs) has become more and more important with the booming of diverse location based services. AP localization accuracy heavily relies on the locations of measurement points. However, collecting abundant information from the APs usually requires tremendous manual efforts, which greatly compromise the efficiency and accuracy of the localization of the APs. Thus, the selection of appropriate measurement points becomes an important issue to achieve a high localization accuracy with a low-cost method, which has not been fully explored in existing research. To this end, we propose a novel approach to select measurement points for AP localization under the assumption that the number of APs to be located is known in advance. Specifically, an initial point is selected randomly and the locations of APs are estimated according to the measured information. Then, subsequent measurement points are determined by locating the intersection of the coverage areas of APs in real time, so that as many APs as possible can be detected at each measurement point. Both simulation and experimental results show that our approach can reduce the number of measurement points while improving the AP localization accuracy.