Interval Kalman filter based RFID indoor positioning

Abstract

Radio Frequency Identification (RFID) technology has shown its potential in the field of indoor positioning in recent years, and has been widely used in large establishments such as the airport lobby, supermarkets, libraries, underground parking and so on. However, the complexity of the indoor environments make positioning a challenging problem in terms of accuracy, stability, reliability, and interference immunity. In this paper, we develop an algorithm of passive RFID indoor positioning based on interval Kalman filter, according to the geometric constraints of responding tags, combined with the target motion information. The interval Kalman filter is adopted to integrate target position of one preceding time point and reference tags position to estimate the current position. Advantage of this algorithm is to use passive tags to reduce hardware costs, and on the other hand the introduction of filtering algorithm improves the positioning accuracy.