부산대학교 도서관

We present a novel approach to spectral estimation, posing power spectrum density (PSD) estimation as a constrained optimization problem. More precisely, we optimize the coefficients of a finite impulse response filter such that the output variance is maximized. An analytical solution for this optimization problem is provided and we show that its solution establishes an unbiased estimator for the PSD from which the autocorrelation function and the moving average model coefficients can be derived. The performance of these estimators is demonstrated by comparison to a variety of established methods. Finally, our closed form solution allows interesting theoretical insights and an implementation based on the fast Fourier transform, leading to a fast and accurate estimator.