An entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise

In this paper, we present an entropy based approach for DOA estimation in Gaussian and non-Gaussian environments. The DOA estimates are obtained by minimizing an entropy measure of the array data in the noise subspace. We show that the entropy approach leads to the MAP algorithm under the Gaussian assumption. Under the non-Gaussian assumption, we apply the varimax norm as an information measure. An intuitive consistency analysis is also performed. Computer simulations are used to demonstrate the effectiveness of the proposed approach.