Fingerprint-MDS based algorithm for indoor wireless localization

Indoor wireless localization has emerged as a key wireless network technology and has been used for a variety of applications. In this paper, we examine the possibility to use one RF-based fingerprint system for indoor wireless localization, and show that there is room for improvement in its location sensing approach. We propose an indoor wireless localization solution by improving a fingerprinting localization algorithm with Multidimensional Scaling (MDS). In our approach, we configure RFID readers to receive signal strengths from both RFID tags and reference points, and use a fingerprinting localization algorithm for initial location estimation. We preprocess the received signal strength information to obtain the pairwise distances' estimation between the RFID tags and the reference points. Having estimated the pairwise squared distances, we apply MDS to reconstruct the RFID tags' distribution, and we subsequently use Procrustes analysis to refine the previously obtained fingerprinting location estimation. Simulation results show that our proposed localization algorithm improves the localization accuracy of the fingerprinting approach under different wireless network conditions.