Recursive EM algorithm for stochastic ML DOA estimation

In this work the recursive EM algorithm is studied under the framework of array processing. The recursive EM algorithm is a stochastic approximation procedure with a special gain matrix. Under proper conditions, this procedure leads to strong consistency and asymptotic normality. Using a stochastic signal model, we have derived the recursive EM algorithm to find ML DOA estimates. In contrast to existing methods of finding ML estimates, the proposed method provides a quick update of the estimate as a new data enters. In addition, it can be applied to both narrow band and wideband signals. Numerical results show that the proposed algorithm performs well for closely located sources and low SNRs. This demonstrates the potential of the suggested algorithm in real time processing.