Abstract
In [1], we studied amplitude estimation of one-dimensional (1-D) sinusoidal signals from measurements corrupted by possibly colored observation noise. We herein extend the results for two-dimensional (2-D) amplitude estimation. In particular, we investigate the 2-D sinusoidal amplitude estimation within the general frameworks of least squares (LS), weighted least squares (WLS), and MAtched FIlterbank (MAFI) estimation. A variety of 2-D amplitude estimators are presented, which are all asymptotically statistically efficient. The performances of these estimators in finite samples are compared numerically with one another. Making use of amplitude estimation techniques, we introduce a new scheme for 2-D system identification, which is shown to be computationally simpler and statistically more accurate than the conventional output error method (OEM), when the observation noise is colored.
Original language | English |
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Pages (from-to) | 1921-1924 |
Number of pages | 4 |
Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Volume | 3 |
State | Published - 2001 |
Event | 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States Duration: 7 May 2001 → 11 May 2001 |