A complex convex relaxation for approximate maximum likelihood 2D energy-based source localization in sensor networks

This paper addresses the energy-based self-localization problem in wireless sensor networks. An approximate solution to the maximum likelihood location estimation problem is presented, by redefining the problem in the complex plane and relaxing the minimization problem into semidefinite programming form. Simulation results show that the presented method is effective at moderate to high noise levels.