A simple method for DOA estimation in the presence of unknown nonuniform noise

When considering the problem of direction-of-arrival (DOA) estimation, uniform noise is often assumed and hence, the corresponding noise covariance matrix is diagonal and has identical diagonal entries. However, this does not always hold true since the noise is nonuniform in certain applications and a model of arbitrary diagonal noise covariance matrix should be adopted. To this end, a simple approach to handling the unknown nonuniform noise problem is proposed. In particular, an iterative procedure is developed to determine the signal subspace and noise covariance matrix. As a consequence, existing subspace-based DOA estimators such as MUSIC can be applied. Furthermore, the proposed method converges within very few iterations, in each of which closed-form estimates of the signal subspace and noise covariance matrix can be achieved. Hence, it is much more computationally attractive than conventional methods which rely on multi-dimensional search. It is shown that the proposed method enjoys good performance, simplicity and low computational cost, which are desirable in practical applications.