Two dimensional high-resolution spectral estimator with singular covariance matrix

Employing singular covariance matrix, spectral estimation methods can give high resolution results. In this paper, the original one-dimensional (1-D) spectral estimation method, which is based on singular covariance matrix, is extended to the case of two-dimensional (2-D). With the few snapshots, forward-backward method is utilized to calculate the sample covariance matrix. Owing to the better estimate of the sample covariance matrix, the new method can give good performance on the estimation accuracy of the 2-D spectrum. Simulation results show that the proposed method is superior to other similar methods for spectral estimation.