In this paper, we analyze the Cramér-Rao Lower Bound (CRLB) of localization using Signal Strength Difference (SSD) as location fingerprint. This analysis has a dual purpose. Firstly, the properties of the bound on localization error may help in designing efficient localization algorithms. For example, utilizing one of the properties, we propose a way to define weights for a weighted K-Nearest Neighbor (K-NN) scheme which is shown to perform better than the K-NN algorithm. Secondly, it provides suggestions for a positioning system design by revealing error trends associated with the system deployment. In both cases, detailed analysis as well as experimental results are presented in order to support our claims.
Similarly, the authors in REF analyzed the CRLB of the localization by selecting the Signal Strength Difference (SSD) as the location fingerprint.
Cramer-Rao Bound Analysis of Localization Using Signal Strength Difference as Location Fingerprint
2010 Proceedings IEEE INFOCOM
2010 Proceedings IEEE INFOCOM
Computer Science