TOA Based Localization Under NLOS in Cognitive Radio Network

In this paper, we consider cooperative localization of primary users (PU) in a cognitive radio network (CRN) using time-of-arrival (TOA). A two-step none-line-of-sight (NLOS) identification algorithm is proposed for the situation where both NLOS error distribution and channel model are not available. In the first step the TOA measurements are clustered into groups. The groups with a dispersion higher than a predefined threshold are identified as NLOS and discarded. In order to make the threshold more reasonable, Ostu’s method, a threshold selection method for image processing is utilized. The second step is introduced to correct the error of possible surviving NLOS. To increase the accuracy of estimated position when line-of-sight (LOS) paths are limited, we proposed a result reconstruction method. Simulation results show that our algorithm can effectively identify NLOS paths and improve positioning accuracy compared to existing works.