DOA Estimation with Few Snapshots Based on Iterative Adaptive Approach and Eigenvalue Decomposition

Abstract

Direction of arrival (DOA) estimation is one of the goals of array signal processing. In this paper, we propose a new approach for DOA estimation in the scenario with only few snapshots. The DOA estimation can be considered as a sparse parameter estimation problem. In order to reduce the influence of a small number of snapshots, we calculate the covariance matrix by iterative adaptive approach (IAA). Based on the orthogonality between signal subspace and noise subspace, the eigenvalue decomposition is performed on the covariance matrix. After constructing a spectral function, the DOA of each source can be estimated from the peaks of the function. An important advantage is that, the proposed method does not need any hyperparameter. The results of numerical simulations demonstrate that the proposed method has very low and stable sidelobes, and it also obtains more accurate estimation and higher resolution than several classical algorithms.