A MLE-PSO indoor localization algorithm based on RSSI

Abstract

Received signal strength indicator (RSSI) are mostly used to measure distance in wireless sensor networks (WSNs). It is difficult to avoid the error of RSSI ranging due to the complexity of the indoor environment. However, the localization error of the existing localization algorithm will increase greatly with the increase of ranging error. In order to improve the positioning accuracy, stability as well as the dynamic performance of localization, a MLE-PSO indoor localization algorithm based on RSSI is proposed in this paper. This new algorithm uses an optimization algorithm the traditional particle swarm optimization (PSO) for localization, and uses a traditional localization algorithm maximum likelihood estimation (MLE) to confine initial range and the area iterative process of PSO localization process. Simulation results show that the new algorithm improves the positioning accuracy and dynamic performance effectively compared with the PSO and MLE.