Nonlinear methods of spectral analysis have become widely used for improving the arrival-angle resolving power of signals from observed targets situated in the far zone of scanning systems utilizing equidistant linear antenna arrays (AA). Among them, the greatest popularity has been earned by methods of autoregressive estimation of the space spectrum (SS) directly from a sample of observations without estimation of the covariational matrix. The present work performs a comparative analysis and makes recommendations with regard to two methods: the maximum-entropy method (MEM) developed by Burg and the linear-prediction method (LPM) based on an algorithm advanced by Kumaresan and Tafts (see [1])
To process data obtained during interference experiments in high-energy physics, methods of spectral...
The Burg maximum entropy method and the LPSVD modeling method have been applied to solid-state spect...
Abstract: Mathematical analysis of the behavior of general dynamic systems based on linear predictio...
A new spectral estimate, the maximum entropy method, is described. In the maximum entropy method, th...
Multidimensional random fields are considered in the paper aiming at the development of theoretical-...
Array processing for spatial spectrum estimation is reexamined from the vector space viewpoint with ...
Several algorithms have been used in maximum entropy spectral analysis. Among them, the standard Bur...
Special attention has been given to “super-decisive” methods of spectral estimation [1–15] in the li...
The problem of estimating the distribution of energy arriving at an array as a function of bearing i...
Spectrum estimation belongs to the most frequent problems solved by the digital stochastic signal pr...
Traditional maximum entropy spectral estimation determines a power spectrum from covariance estimate...
A general algorithm of slit spectra extraction for a system of point-like sources (e.g. multiple len...
In recent research on AA theory one of the major issues is elaboration of methods for estimation of ...
Over the past 10 years, spectral analysis has been shown to have the potential to be a reliable mean...
The nonlinear behavior of the filter-type Maximum Entropy Method (MEM) was investigated from a theor...
To process data obtained during interference experiments in high-energy physics, methods of spectral...
The Burg maximum entropy method and the LPSVD modeling method have been applied to solid-state spect...
Abstract: Mathematical analysis of the behavior of general dynamic systems based on linear predictio...
A new spectral estimate, the maximum entropy method, is described. In the maximum entropy method, th...
Multidimensional random fields are considered in the paper aiming at the development of theoretical-...
Array processing for spatial spectrum estimation is reexamined from the vector space viewpoint with ...
Several algorithms have been used in maximum entropy spectral analysis. Among them, the standard Bur...
Special attention has been given to “super-decisive” methods of spectral estimation [1–15] in the li...
The problem of estimating the distribution of energy arriving at an array as a function of bearing i...
Spectrum estimation belongs to the most frequent problems solved by the digital stochastic signal pr...
Traditional maximum entropy spectral estimation determines a power spectrum from covariance estimate...
A general algorithm of slit spectra extraction for a system of point-like sources (e.g. multiple len...
In recent research on AA theory one of the major issues is elaboration of methods for estimation of ...
Over the past 10 years, spectral analysis has been shown to have the potential to be a reliable mean...
The nonlinear behavior of the filter-type Maximum Entropy Method (MEM) was investigated from a theor...
To process data obtained during interference experiments in high-energy physics, methods of spectral...
The Burg maximum entropy method and the LPSVD modeling method have been applied to solid-state spect...
Abstract: Mathematical analysis of the behavior of general dynamic systems based on linear predictio...