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A state space approach for the 2-D harmonic retrieval problem

In this paper, a State Space approach to the 2-D harmonic retrieval problem is presented. Under certain assumptions, it is shown that the data and covariance matrices have finite rank and also possess a desirable algebraic structure. Then methods employing the Principal components algorithm are developed to estimate the state space parameters and the sinusoid parameters directly from the data and from the covariance information. Simulation results to support the methods are also provided.