  In this work, we propose a subspace-based algorithm for direction-of-arrival
(DOA) estimation, referred to as two-step knowledge-aided iterative estimation
of signal parameters via rotational invariance techniques (ESPRIT) method
(Two-Step KAI-ESPRIT), which achieves more accurate estimates than those of
prior art. The proposed Two-Step KAI-ESPRIT improves the estimation of the
covariance matrix of the input data by incorporating prior knowledge of signals
and by exploiting knowledge of the structure of the covariance matrix and its
perturbation terms. Simulation results illustrate the improvement achieved by
the proposed method.
