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

  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.},
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
2-D Sinusoidal Amplitude Estimation with Application to 2-D System Identification ∗
In a companion paper [1], we studied amplitude estimation of one-dimensional (1-D) sinusoidal signals from measurements corrupted by possibly colored observation noise. We herein extend the resultsExpand
2D sinusoidal amplitude estimation with application to 2D system identification
  • Hongbin Li, W. Sun, P. Stoica, J. Li
  • Computer Science, Mathematics
  • 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)
  • 2001
A new scheme for 2D system identification is introduced, which is shown to be computationally simpler and statistically more accurate than the conventional output error method (OEM), when the observation noise is colored. Expand
Efficient Iterative Frequency Estimator of Sinusoidal Signal in Noise
This paper proposes an efficient iterative estimation algorithm using the phase shift Fourier interpolation and derives the performance of the new estimator, which is asymptotically unbiased and its mean squared error is slightly above the asymPTotical Cramer-Rao bound over the whole frequency estimation range. Expand
Iterative Estimation of Sinusoidal Signal Parameters
Experiments conducted on synthetic and speech signals show the suggested model's effectiveness in correcting frequency estimation errors and robustness in additive noise conditions. Expand
A new approach to single-tone frequency estimation via linear least squares curve fitting
The mathematical basis of this algorithm is described, and the bias and variance are analyzed analytically and numerically and it will be demonstrated that performance is comparable to a digital phase locked loop, with some stability and tracking range advantages. Expand
New Procedure for Estimation of Amplitude and Phase of Analog Multiharmonic Signal Based on the Differential Irregular Samples
  • P. Petrovic
  • Computer Science, Mathematics
  • J. Signal Process. Syst.
  • 2015
It is proved that the estimation performance of the proposed algorithm can attain Cramer-Rao lower bound (CRLB) for sufficiently high signal-to-noise ratios. Expand
Algorithm for signal parameters estimation based on the differential samples
This paper is concerned with the estimation of amplitude and phase of an analog multi-harmonic signal based on a series of differential values of the signal. To this end, assuming the signalExpand
Reliable amplitude and frequency estimation for biased and noisy signals
Abstract Robust estimation of the amplitude, frequency and bias of unknown noisy sinusoidal signals is considered in this paper. It is only assumed that the measurements noise is bounded without anyExpand
This chapter provides a review of some of the existing work in the area of nonparametric spectral estimation, including fast implementations of the most successful estimators as well as various extensions to spectral analysis of incomplete data. Expand
Some New Results on the Estimation of Sinusoids in Noise
The main focus has not been on developing new algorithms for specific applications, but rather on understanding the underlying estimation problem and analysing it in a consistent fashion. Expand


Performance analysis of forward-backward matched-filterbank spectral estimators
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
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
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
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
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