Modeling sensor position uncertainty for robust target localization in wireless sensor networks

In wireless sensor networks, sensor position uncertainty degrades the accuracy of the energy-based target localization achieved using maximum likelihood estimation (MLE) methods. In this paper, we developed a new MLE approach that incorporates a model of sensor position uncertainty. Simulations demonstrated that our new MLE approach outperformed an MLE approach that does not account for sensor position uncertainty. Root-mean-square (RMS) estimation errors for target localization were close to the Cramer-Rao lower bound (CRLB).