Direction-of-Arrival Estimation using a Low-Complexity Covariance-Based Approach


This text presents a new algorithm for performing direction-of-arrival (DOA) estimation using manipulations on covariance matrices. The proposed algorithm combines a replacement formulation for information projection on real subspaces, along with beamspace decompositions, reducing the sizes of all knowledge structures and computational complexity of the resulting estimation method. Theoretical analyses and computer simulations indicate that the proposed algorithm reduces its ESPRIT equivalent computational complexity by no less than twenty%, while presenting similar mean-sq. error (MSE) performance.

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