Abstract: The ranging error of WSN (wireless sensor network) is usually large in complex environments. We find that the elements of the coordinate inner product matrix may fluctuate in a certain range with the changing ranging error. Therefore, we present a maximum likelihood estimation (MLE) location algorithm based on the coordinate inner product matrix for determining the relative locations of sensor nodes in complex environments with large ranging error. Based on the global topological structure and the connectivity of WSNs, the geodesic distance between each node and the coordinate inner product matrix are obtained. Using the maximum likelihood estimator for a coordinate inner product matrix, we can finally estimate the sensor node coordinates by finding the global optimal solution. The experimental results show that the algorithm has good noise resistance for ranging noise; therefore, it is suitable for WSN node locating with large range noise. When the node distance error is large, it can also achieve high location accuracy.

Key words: wireless sensor network, node, location algorithm, maximum likelihood estimate