Acoustic Source DOA Estimation using the Cross-Entropy Method

This paper deals with the problem of estimating the directions-of-arrival (DOA) of multiple wideband sources using an array of sensors. While a variety of estimation techniques have been proposed in the literature, the maximum-likelihood (ML) DOA estimator has been shown to have superior performance under many challenging environments. In this paper, we propose a novel implementation for ML DOA estimator based on the cross-entropy (CE) method. Simulation results show the CE algorithm converges to the Cramer-Rao bound (CRB) in all scenarios within several iterations and the convergence speed is insensitive to the coherence of sources.