Estimation of the Variance of a Random Signal with an Unknown Frequency Bandwidth

We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-likelihood algorithm and the joint maximum-likeli...

Full description

Saved in:
Bibliographic Details
Published inRadiophysics and quantum electronics Vol. 65; no. 11; pp. 862 - 875
Main Authors Korchagin, Yu. E., Turbin, M. M., Titov, K. D.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2023
Springer
Springer Nature B.V
Subjects
Algorithms
Analysis
Astronomy
Astrophysics and Astroparticles
Density
Distribution (Probability theory)
Hadrons
Heavy Ions
Lasers
Mathematical and Computational Physics
Maximum likelihood estimation
Nuclear Physics
Observations and Techniques
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
Quantum Optics
Random signals
Theoretical
Variance
Online AccessGet full text

Cover

More Information
Summary:We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-likelihood algorithm and the joint maximum-likelihood estimation of all unknown parameters. The structural schemes are developed and the estimation characteristics are found for the synthesized algorithms. The estimation-accuracy loss because of the a priori ignorance of the spectral-density width of a useful signal are determined.
ISSN:0033-8443
1573-9120
DOI:10.1007/s11141-023-10262-y