Amplitude estimation of sinusoidal signals: survey, new results, and an application

@article{Stoica2000AmplitudeEO,
  title={Amplitude estimation of sinusoidal signals: survey, new results, and an application},
  author={Petre Stoica and Hongbin Li and Jian Li},
  journal={IEEE Trans. Signal Process.},
  year={2000},
  volume={48},
  pages={338-352}
}
This paper considers the problem of amplitude estimation of sinusoidal signals from observations corrupted by colored noise. A relatively large number of amplitude estimators, which encompass least squares (LS) and weighted least squares (WLS) methods, are described. Additionally, filterbank approaches, which are widely used for spectral analysis, are extended to amplitude estimation; more exactly, we consider the matched-filterbank (MAFI) approach and show that by appropriately designing the… Expand
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References

SHOWING 1-10 OF 17 REFERENCES
Performance analysis of forward-backward matched-filterbank spectral estimators
TLDR
It is shown by means of a higher order expansion technique that the one-dimensional (1-D) Capon estimator underestimates the true spectrum, whereas the 1-D APES method is unbiased; it is shown that the bias of the forward-backward Capon is half that of theforward-only Capon (to within a second-order approximation). Expand
An adaptive filtering approach to spectral estimation and SAR imaging
TLDR
It is shown via both numerical and experimental examples that the adaptive FIR filtering approaches such as Capon and APES can yield more accurate spectral estimates with much lower sidelobes and narrower spectral peaks than the FFT method, which is also a special case of the FIR filtering approach. Expand
Capon and APES spectrum estimation for real-valued signals
This paper considers the problem of estimating the spectrum of real-valued signals. We propose real-valued versions of the Capon and the APES spectral estimators. The estimators are derived asExpand
DATA ADAPTIVE SPECTRAL ANALYSIS METHODS
Two new methods (Maximum Likelihood Method or MLM, and Maximum Entropy Method or MEM) for power spectral density estimation have been experimentally investigated. Both methods, unlike conventionalExpand
High-resolution frequency-wavenumber spectrum analysis
The output of an array of sansors is considered to be a homogeneous random field. In this case there is a spectral representation for this field, similar to that for stationary random processes,Expand
Matched-filter bank interpretation of some spectral estimators
TLDR
This work makes use of a matched-filter bank (MAFI) approach to derive spectral estimators for stationary signals with mixed spectra and shows that the Capon spectral estimator as well as the more recently more recently Capon spectra estimator are derived. Expand
On output-error methods for system identification
In this paper are derived consistency and asymptotic normality results for the output-error method of system identification. The output-error estimator has the advantage over the prediction-errorExpand
On reparametrization of loss functions used in estimation and the invariance principle
Abstract The problem addressed in this note concerns the relationship between the minimizers of a given loss function parametrized in two different ways. The so-called “invariance principle” (IP)Expand
Convergence rates for inverse Toeplitz matrix forms
Given a p-dimensional spectral density [phi]([omega])>=cI>0, [for all][omega][set membership, variant][0,2[pi]] such that [phi]r([omega]) [set membership, variant] Lip* ([alpha]), with covarianceExpand
Introduction to spectral analysis
TLDR
This chapter presents a meta-analyses of the nonparametric methods used in the construction of the Cramer-Rao Bound Tools, which were developed in the second half of the 1990s to address the problem of boundedness in the discrete-time model. Expand
...
1
2
...