The letter deals with direction-of-arrival (DOA) estimation under nonuniform white noise and moderately small signal-to-noise ratios. The proposed approach first uses signal subspace projection for received data vectors, which form an efficient iterative quadratic maximum-likelihood (IQML) approach to achieve fast convergence and high resolution capabilities. In conjunction with a signal subspace selection technique, a more exact signal subspace can be obtained for reducing the nonuniform noise effect. The performance improvement achieved by applying the proposal to the classic IQML method is confirmed by computer simulations.

In conjunction with a first-order Taylor series approximation of the spatial scanning vector, this letter presents an iterative multiple signal classification (MUSIC) direction-of-arrival (DOA) estimation for code-division multiple access signals. This approach leads to a simple one-dimensional optimization problem to find each iterative optimal search grid. It can not only accurately estimate DOA, but also speed up the estimating process. Computer results demonstrate the effectiveness of the proposed algorithm.