Optimally Weighted MUSIC for Frequency Estimation
Petre Stoica, Anders Eriksson, Torsten Söderström · SIAM Journal on Matrix Analysis and Applications · 1995
This paper introduces a weighted MUSIC (multiple signal classification) algorithm for estimating the frequencies of sinusoidal signals from noise-corrupted measurements. The large-sample variance of the weighted MUSIC is determined, and the optimal weighting matrix which minimizes that variance is derived. The optimally weighted MUSIC is shown to provide more accurate frequency estimates than the unweighted MUSIC and ESPRIT (estimation of signal parameters via rotation invariance techniques).