Relative Location Estimation Algorithm Based on Coordinates Inner Product Matrix-Based Maximum Likelihood

We present a relative location estimation algorithm based on the coordinates inner product matrix-based maximum likelihood (CML) for determining the relative locations of sensor nodes in wireless sensor networks. We use the geodesic distance between each node to obtain the coordinates inner product matrix, then derive the maximum-likelihood estimator for coordinates inner product matrix to estimate the coordinates of sensor nodes. The simulation results show that the proposed algorithm outperforms existing solutions in terms of the location accuracy in wireless sensor networks.