Distance-based maximum likelihood estimation method for node localization in wireless sensor networks

Node localization is an important supporting technique in wireless sensor networks (WSNs). The traditional maximum likelihood estimation localization method (MLE) assumes that measurement errors are independent of the distance between anchor node and target node. However, the assumption may contradict with the physical characteristic of some existing measurement techniques, such as the widely-used received signal strength indicator. To address this issue, we propose a distance-based MLE considering the dependence of measurement errors on the distance. The proposed distance-based MLE is formulated as a complicated nonlinear optimization problem. An exact solution method is presented based on first order optimal conditional and to improve the search efficiency, a two-dimensional search method is also given. Simulation experiments are performed to demonstrate the effectiveness of this localization. The simulation results show that the distance-based localization method has better localization accuracy compared with other range-based localization methods

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