  A general non-Gaussian semiparametric model is adopted to characterize the
measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array.
Moreover, the recently derived \textit{robust semiparametric efficient}
$R$-estimator of the data covariance matrix is exploited to implement an
original version of the MUSIC estimator. The efficiency of the resulting
$R$-MUSIC algorithm is investigated by comparing its Mean Squared Error (MSE)
in the estimation of the source spatial frequencies with the relevant
Semiparametric Stochastic Cram\'{e}r-Rao Bound (SSCRB).
