Exponential energy spectral density estimation
L. Marple
Abstract
L. Marple
Abstract
A new spectral estimation is presented as an alternative to the popular autoregressive (maximum entropy) spectrum analysis methods. This technique maintains the high resolution properties of the autoregressive (AR) technique for high signal-to-noise ratios; it produces a spectrum whose output is linearly proportional to the power (energy), unlike the AR method whose output is nonlinearly related to power. The estimate, termed an exponential energy spectral density (ESD), has the ability to model both sharp and broadband spectra. Examples with doppler radar data are shown.
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A new spectral estimation is presented as an alternative to the popular autoregressive (maximum entropy) spectrum analysis methods. This technique maintains the high resolution properties of the autoregressive (AR) technique for high signal-to-noise ratios; it produces a spectrum whose output is linearly proportional to the power (energy), unlike the AR method whose output is nonlinearly related to power. The estimate, termed an exponential energy spectral density (ESD), has the ability to model both sharp and broadband spectra. Examples with doppler radar data are shown.
Key concepts: Autoregressive model, Maximum entropy spectral estimation, Spectral density, Spectral density estimation, Exponential function, Energy (signal processing), Radar, Entropy (arrow of time)