| Paper: | SPTM-L4.4 | ||
| Session: | Frequency Estimation | ||
| Time: | Wednesday, May 17, 11:00 - 11:20 | ||
| Presentation: | Lecture | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications | ||
| Title: | Model Order Selection Rule for Estimating the Parameters of 2-D Sinusoids in Colored Noise | ||
| Authors: | Mark Kliger, Joseph M. Francos, Ben-Gurion University, Israel | ||
| Abstract: | We consider the problem of jointly estimating the number as well as the parameters of 2-D sinusoidal signals, observed in the presence of an additive colored noise field. In this framework we consider the problem of least squares estimation of the parameters of 2-D sinusoidal signals observed in the presence of an additive noise field, when the assumed number of sinusoids is incorrect. In the case where the number of sinusoidal signals is under-estimated we show the strong convergence of the least squares estimates to the parameters of the dominant sinusoids. In the case where the number of sinusoidal signals is over-estimated, the estimated parameter vector obtained by the least squares estimator contains a sub-vector that converges to the correct parameters of the sinusoids. Based on these results, we prove the strong consistency of a large family of model order selection rules. | ||
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