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MUltiple SIgnal Classification (MUSIC) is an algorithm used for frequency estimation and emitter location .== Application to frequency estimation ==

MUSIC estimates the frequency content of a signal or autocorrelation matrix using an eigenspace method. This method assumes that a signal, $x(n)$, consists of $p$ complex exponentials in the presence of Gaussian white noise. Given an $M\; \backslash times\; M$ autocorrelation matrix, $\backslash mathbf\{R\}\_x$, if the eigenvalues are sorted in decreasing order, the eigenvectors corresponding to the $p$ largest eigenvalues spanning the signal subspace. Note that for $M\; =\; p\; +\; 1$, MUSIC is identical to Pisarenko's method. The general idea is to use averaging to improve the performance of the Pisarenko's estimator.

The frequency estimation function for MUSIC is

where $\backslash mathbf\{v\}\_i$ are the noise eigenvectors and

History

MUSIC was originated by R. O. Schmidt in 1979 as an improvement to Pisarenko's method.