Kalman filters for reducing error in RFID real-time localization systems

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology for this purpose experience localization errors due to noise and non-line-of-sight effects inherent to these environments. This paper presents the use of both linear and non-linear Kalman filters to reduce error effects inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a mathematical model and approach are developed. The model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw distance difference of arrival measurements as well as final trilateration results.