A practical complete MLE cooperative localization solution

Among existing classical cooperative localization techniques for wireless sensor networks, the maximum likelihood estimator (MLE) is theoretically the best in the sense that it asymptotically achieves the Cramér-Rao bound (CRB). However, the gradient based iterative algorithms that are commonly used to achieve ML estimated positions are quite sensitive to the initial values and cannot achieve the theoretic optimal performance. In this paper, we propose a complete MLE solution, named “MLE-MLE”, where a non-cooperative or single node MLE is first applied to generate the initial values for the iterative MLE cooperative localization algorithm. The inherent unimodal property of the single node log-likelihood guarantees that single node MLE method converges to the unique solution whatever the starting point is. As verified by numerical results, among existing practical classical cooperative location estimators, MLE-MLE is the best whose performance is closest to CRB.