TY - JOUR
T1 - MPLITUDE ESTIMATION WITH APPLICATION TO SYSTEM IDENTIFICATION
AU - Stoica, Petre
AU - Li, Hongbin
AU - Li, Jian
N1 - Publisher Copyright:
© 1999 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 1999
Y1 - 1999
N2 - We investigate herein the problem of amplitude estimation of sinusoidal signals from observations corrupted by colored noise. A relatively large number of amplitude estimators are described which encompass Least Squares (LS) and Weighted Least Squares (WLS) methods. Additionally, filterbank approaches, which are widely used for spectral analysis, are extended to amplitude estimation. Specifically, we consider the recently introduced MAtched-FIlterbank (MAFI) approach and show that, by appropriately designing the prefilters, the MAFI approach includes the WLS approach. The amplitude estimation techniques discussed in this paper do not model the noise, and yet they are all asymptotically statistically efficient. It is their different finite-sample properties that are of particular interest to this study. Nurnericd examples are provided to illustrate the differences among the various estimators. Though amplitude estimation applications are numerous, we focus on system identification using sinusoidal probing signals.
AB - We investigate herein the problem of amplitude estimation of sinusoidal signals from observations corrupted by colored noise. A relatively large number of amplitude estimators are described which encompass Least Squares (LS) and Weighted Least Squares (WLS) methods. Additionally, filterbank approaches, which are widely used for spectral analysis, are extended to amplitude estimation. Specifically, we consider the recently introduced MAtched-FIlterbank (MAFI) approach and show that, by appropriately designing the prefilters, the MAFI approach includes the WLS approach. The amplitude estimation techniques discussed in this paper do not model the noise, and yet they are all asymptotically statistically efficient. It is their different finite-sample properties that are of particular interest to this study. Nurnericd examples are provided to illustrate the differences among the various estimators. Though amplitude estimation applications are numerous, we focus on system identification using sinusoidal probing signals.
UR - http://www.scopus.com/inward/record.url?scp=76849098383&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=76849098383&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.1999.758264
DO - 10.1109/ICASSP.1999.758264
M3 - Conference article
AN - SCOPUS:76849098383
SN - 1520-6149
VL - 4
SP - 1777
EP - 1780
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
T2 - Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99)
Y2 - 15 March 1999 through 19 March 1999
ER -