RFID indoor positioning based on probabilistic RFID map and Kalman Filtering

Radio Frequency Identification (RFID) is a rapidly developing technology which uses wireless communication for automatic identification of objects. The localization of RFID tagged objects in their environment is becoming an important feature for the ubiquitous computing applications. In This paper we introduce a new positioning algorithm for RFID tags using two mobile RFID readers and landmarks which are passive or active tags with known location and distributed randomly. We present an analytical method for estimating the location of the unknown tag by using the multilateration with the landmarks and a probabilistic RFID map-based technique with Kalman Filtering to enhance the location estimation of the tag. This algorithm is independent from the readers coordinates, and hence it can be more practical due to its mobility and its low cost to achieve a high deployment of this emerging technology. Results obtained after conducting extensive simulations demonstrate the validity and suitability of the proposed algorithm to provide high performance level in terms of accuracy and scalability.