Localization in Wireless Networks with Post-improvement Using Estimation of Distances Between Unknown Nodes: Simulation and Experimental Evaluation

Localization is one of the most crucial issues for many applications. In this paper, several novel algorithms for the a posteriori improvement of the localization results in wireless networks are presented. All introduced algorithms extend the concept of Universal Improvement Scheme (UnIS) presented in our previous work. UnIS uses additional information about the network available during the localization. One concrete solution is represented by distances between couples of mobile nodes being localized. According to our concept, a corresponding mathematical model is being developed and simulated on the appropriate simulation platform. The outcome from the simulations is being validated by the empirical results obtained in a deployed wireless sensor network. Additionally, UnIS refinement is being compared to a well-known Kalman Filter technique.