A New Method for Estimating the Direction-of-Arrival Waves by an Iterative Subspace-Based Method

─ In this paper, a new subspace-based method for high-resolution direction-of-arrival (DOA) estimation of multiple plane waves in a noisy environment is proposed. This method called Iterative-Subspace-Decomposition (ISD) involves an iterative decomposition into two blocks of the matrices corresponding to the noise and the source subspaces. The proposed algorithm provides enhanced estimation performance of the DOA. It also significantly improves the resolution capability with respect to existing algorithms. The method can be applied to low signal-to-noise ratio (SNR) environment and is suitable for arrays with arbitrary sensor geometries, including linear arrays. Several numerical simulations are presented to assess the proposed method enhanced performance in comparison to that obtained by some classical algorithms. This comparative study has shown that the ISD leads to a significant reduction in the Root Mean Square Errors (RMSE) and resolution rate capabilities of the DOA estimates. As though, it is shown that the ISD method is superior in resolving closely spaced signals with a small number of snapshots and at low SNR. Index Terms─ Subspace-based methods, DOA estimation, iterative decomposition, highresolution capability, estimation performance, arbitrary sensor geometries, linear arrays.