Complexity-reduced direction-of-arrival estimation method for highly correlated sources

The paper presents an approach based on a preprocessing technique that allo ws previously known methods of reducing the complexity of subspace-based me thods to be adapted to the case of highly correlated signals. Snapshot vect ors are first preprocessed, and then used to compute the signal subspace of the spatially smoothed correlation matrix. The proposed method is a comple xity-reduced version of the DEESE algorithm (Grenier et al., 1993). It give s better resolution in noisy environments than the common spatial-smoothing method with a relatively small increase in computational cost.