2-D sinusoidal amplitude estimation with application to 2-D system identification

H. Li, W. Sun, P. Stoica, J. Li

Research output: Contribution to journalConference articlepeer-review

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 languageEnglish
Pages (from-to)1921-1924
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
StatePublished - 2001
Event2001 IEEE International Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
Duration: 7 May 200111 May 2001

Fingerprint

Dive into the research topics of '2-D sinusoidal amplitude estimation with application to 2-D system identification'. Together they form a unique fingerprint.

Cite this