Enhancing the Accuracy of Indoor Positioning Using System Delay Time Compensation

Abstract

Indoor positioning based on the Hidden Markov Model (HMM), which utilizes a combination of Received Signal Strength Indicator (RSSI) from Access Points (APs) and inertial sensors, has been exploited broadly due to its superiority compared to other approaches. Some previous studies, which have utilized a combination of two methods, have often assumed the users do not move in the system estimated time and normally this time has been neglected. However, when the number of reference points is huge, and the user moves a considerable distance, the computational time of the system increases considerably. In this case, the system computational time can not be canceled. This paper presents an approach to improving the accuracy of the positioning system. By considering the processing time of the system when it estimated the position of the user, and then cooperating the measured information from the inertial sensor, the localization of the user is estimated more accurately. The simulation results show that the proposed approach achieves a remarkable effect compared to previous studies with the same scenario even if the user moves or does not move in a large area.