TY - JOUR
T1 - Amplitude estimation for sinusoidal signals with application to system identification
AU - Stoica, Petre
AU - Li, Hongbin
AU - Li, Jian
PY - 1999
Y1 - 1999
N2 - This paper considers the problem of amplitude estimation of sinusoidal signals from observations corrupted by colored noise. A relatively large number of amplitude estimators are described that encompass least squares (LS) and weighted least squares (WLS) methods. Additionally, filter bank approaches, which are widely used for spectral analysis, are extended to amplitude estimation. Specifically, we consider the recently introduced matched-fllterbank (MAPI) approach and show that by appropriately designing the prefllters, the MAPI approach to amplitude estimation includes the WLS approach. The amplitude estimation techniques discussed in this paper do not model the observation noise, and yet, they are all asymptotically statistically efficient. It is, however, their different finite-sample properties that are of particular interest to this study. Numerical examples are provided to illustrate the differences among the various amplitude estimators. Although amplitude estimation applications are numerous, we focus herein only on system identification using sinusoidal probing signals.
AB - This paper considers the problem of amplitude estimation of sinusoidal signals from observations corrupted by colored noise. A relatively large number of amplitude estimators are described that encompass least squares (LS) and weighted least squares (WLS) methods. Additionally, filter bank approaches, which are widely used for spectral analysis, are extended to amplitude estimation. Specifically, we consider the recently introduced matched-fllterbank (MAPI) approach and show that by appropriately designing the prefllters, the MAPI approach to amplitude estimation includes the WLS approach. The amplitude estimation techniques discussed in this paper do not model the observation noise, and yet, they are all asymptotically statistically efficient. It is, however, their different finite-sample properties that are of particular interest to this study. Numerical examples are provided to illustrate the differences among the various amplitude estimators. Although amplitude estimation applications are numerous, we focus herein only on system identification using sinusoidal probing signals.
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M3 - Article
AN - SCOPUS:33747641638
SN - 1053-587X
VL - 47
SP - 281
EP - 282
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 1
ER -