An efficient approach for two-dimensional parameter estimation of a single-tone

Abstract--In this paper, parameter estimation of a two-dimensional (2-D) single damped real/complex tone in the presence of additive white Gaussian noise is addressed. By utilizing the rank-one property of the 2-D noise-free data matrix, the damping factor and frequency for each dimension are estimated in a separable manner from the principal left and right singular vectors according to an iterative weighted least squares procedure. The remaining parameters are then obtained straightforwardly using standard least squares. The biases as well as variances of the damping factor and frequency estimates are also derived, which show that they are approximately unbiased and their performance achieves Cram

• Type: Journal
• Year: 2010
• Where: TSP
• Authors: H. C. So, Frankie K. W. Chan, W. H. Lau, Cheung-Fat Chan
• Keywords: 2-D Noise-free Data, Additive White Gaussian Noise, Artificial Intelligence, Damping Factor, TSP 2010