On localizing the source of random signals using sensor networks

The problem of source localization using a network of sensors is considered. A maximum likelihood estimation (MLE) based approach is adopted. The measurements received at the sensors due to the random phenomenon are spatially correlated and are characterized by a multivariate distribution. Using the theory of copulas, the joint parametric density of sensor observations is obtained assuming only the knowledge of their marginal densities. An example showing the efficiency of the proposed approach is presented.