Efficient localization algorithm for wireless sensor networks using Levenberg-Marquardt refinement

Position location has recently been of great interest in wireless technologies due to its crucial role in many applications. In wireless sensor networks, the task of localizing sensor nodes with unknown position is important for the operation and configuration of the network. This significance has simulated research into variety of localization algorithms. In this paper we investigated the nonlinear localization problem with Levenberg-Marquardt (LM) algorithm based on time of arrival (ToA) measurements provided by the anchors. It is shown that the performance of proposed solution achieves significant accuracy and convergence. Cramér-Rao lower bound (CRLB) which is the lower bound on the variance for any localization algorithm is also derived for the proposed approach in the presence of additive Gaussian noise.