Weighted Multilateration Algorithm With a Correcting Factor for Mobile Wireless Sensor Networks

Localization is one of the major problems in mobile wireless sensor networks, since it provides the location of an event occurrence. This paper evaluates the performance of range-based localization algorithms: the multilateration algorithm, the weighted multilateration algorithm, the maximum likelihood algorithm and the multilateration algorithm with a correcting factor. We also propose the weighted multilateration algorithm with a correcting factor through which the localization error is decreased through the addition of a factor that corrects the distance between the node of interest and the reference nodes. Our proposal includes the analysis of noise in the environment due to the time of arrival and the analysis of node of interest's mobility in the calculation of the correlation matrix of the weighted multilateration algorithm and the calculation of the correcting factor. The localization algorithms analyzed in this study are evaluated in a single-hop scenario and a multi-hop scenario considering a well-defined distribution of the reference nodes and a random distribution of these in both scenarios. The results we obtained varying the number of reference nodes and noise proportion prove that the algorithm we propose yields a better performance than the other analyzed algorithms do, according to the normalized root mean squared error.