On least squares methods for direction of arrival estimation in the presence of unknown noise fields

The direction-of-arrival estimation of signal wavefronts in the presence of unknown noise fields is investigated. Generalizations of known criteria for both conditional and nonconditional maximum-likelihood estimates are developed. Numerical calculations show that the usual Gauss-Newton iteration for conditional maximum-likelihood estimates cannot give good results. Therefore, a related, relatively simple two-step least-squares estimate is constructed. Results of numerical experiments are presented and indicate that the two-step estimate has approximately the same power as the least-squares estimate using the exact noise correlation structure