Experimental analysis of RSSI-based location estimation in wireless sensor networks

With a widespread increase in the number of mobile wireless systems and applications, the need for location aware services has risen at a very high pace in the last few years. Much research has been done for the development of new models for location aware systems, but most of it has primarily used the support of 802.11 wireless networks. Less work has been done towards an exhaustive error analysis of the underlying theories and models, especially in an indoor environment using a wireless sensor network. We present a thorough analysis of the Radio Signal Strength (RSS) model for distance estimation in wireless sensor networks through an empirical quantification of error metrics. Further on the basis of this experimental analysis, we implement a k - nearest signal space neighbor match algorithm for location estimation, and evaluate some crucial control parameters using which this technique can be adapted to different cases and scenarios, to achieve finer and more precise location estimates.