An improved RFID-based locating algorithm by eliminating diversity of active tags for indoor environment

The location awareness is a crucial foundation for perceptions of the surroundings in the smart environment. Radio frequency identification (RFID), as one of the most promising technologies, plays a more important role in the indoor location awareness. This paper surveys current RFIDbased locating research and discusses the problem that is brought by the tag's diversity derived from different manufacturer types and different used-time of built-in battery. We present the algorithm named RFDiffFreeLoc to improve the location precision by eliminating the dissimilarity among tags. In the stimulation experiments, we analyze the impact of noise on performance and contrast our algorithm with the existing LANDMARC algorithm. The simulation performances show that our algorithm is feasible via two metrics: the mean error and cumulative error distribution. The results indicate that RFDiffFreeLoc significantly increases the locating accuracy: when the space between the reference tags is 1 m, the mean error drops 0.076-0.344 m according to various noise conditions. Furthermore, a prototype system named RFHome is deployed for validating the algorithm in the actual home environment. The practical experimental results demonstrate that our algorithm is more effective than previous LANDMARC algorithm.