Statistical analysis of an eigendecomposition based method for 2-D frequency estimation

Hua Yang, Yingbo Hua
1994 Automatica  
An eigendecomposition based method for twodimensional frequency estimation is analyzed in this paper. This method, to be referred to as matrix pencil (MP) method, computes a smoothed data covariance matrix, then its eigendecomposition, and then the two-dimensional frequencies via a MP approach. The MP method is now known to be more efficient in computation than many other methods and able to provide a near optimum performance for relatively large signal-to-noise ratio (SNR). The aim of this
more » ... r is to provide a further analysis of the MP method assuming a moderate SNR. To make the problem tractable, a large two-dimensional data set is considered. In this paper, a number of fundamental relations inherent in the MP method are revealed which lead to a general expression of the large-sample covariances of the estimated twodimensional frequencies. The large-sample covariances are reduced to a very simple form for the single two-dimensional frequency case. The theoretical covariances are verified by the simulation results. °
doi:10.1016/0005-1098(94)90235-6 fatcat:vjmgefugbferzkftdcfywbecs4