Two-Dimensional Spectral Estimation by Free Energy Minimization

Abstract

Kiernan, P., Two-Dimensional Spectral Estimation by Free Energy Minimization,Digital Signal Processing6 (1996), 160–168.We present a high-resolution 2-D minimum free energy (MFE) spectral estimation technique which is a 2-D extension of the MFE spectral estimation method. We demonstrate the performance of the technique for spectral estimation of closely spaced 2-D sinusoids in white Gaussian noise. Results from our tests on the effect of signal processing temperature illustrate that our method provides accurate low model order autoregressive spectral estimation. The method provides superior spectral estimation with similar computational burden to that achieved with the Levinson algorithm for a number of cases involving sinusoids in white noise at various signal-to-noise ratio (SNR) levels. An example is provided. The method is faster than the modified covariance method (MCV). An example is given from a number of cases involving two closely spaced sinusoids at low SNR, where MFE estimates are as well resolved as MCV estimates. MFE models may also be used for correlation extension and for field modeling and synthesis. We indicate possible extensions to the MFE method for computational efficiency improvement, a priori temperature determination, and the use of higher-order statistics.