Parameter estimation of superimposed signals using the EM algorithm

We develop a computationally efficient algorithm for parameter estimation of superimposed signals based on the EM algorithm. The idea is to decompose the observed data into their signal components and then to estimate the parameters of each signal component separately. The algorithm iterates back and forth, using the current parameter estimates to decompose the observed data better and thus increase the likelihood of the next parameter estimates. The application of the algorithm to the multipath time delay and to the multiple source location estimation problems is considered.