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The uniform white noise assumption is one of the basic assumptions in most ofthe existing directional-of-arrival (DOA) estimation methods. In manyapplications, however, the non-uniform white noise model is more adequate. Thenthe noise variances at different sensors have to be also estimated as nuisanceparameters while estimating DOAs. In this letter, different from the existingiterative methods that address the problem of non-uniform noise, anon-iterative two-phase subspace-based DOA estimation method is proposed. Thefirst phase of the method is based on estimating the noise subspace viaeigendecomposition (ED) of some properly designed matrix and it avoidsestimating the noise covariance matrix. In the second phase, the resultsachieved in the first phase are used to estimate the noise covariance matrix,followed by estimating the noise subspace via generalized ED. Since theproposed method estimates DOAs in a non-iterative manner, it is computationallymore efficient and has no convergence issues as compared to the existingmethods. Simulation results demonstrate better performance of the proposedmethod as compared to other existing state-of-the-art methods.

Non-Iterative Subspace-Based DOA Estimation in the Presence of Nonuniform Noise