The MUSIC method is widely used in the field of DoA estimation using an array of $M$ sensors, and is known to perform well as long as the number of available samples $N$ is much larger than $M$. Nevertheless, in the scenario where $N$ is of the same order of magnitude than $M$, its performance degrades, essentially because the sample covariance matrix (SCM) is no more a good estimator. A classical improvement, known as "rectification", consists in forcing the SCM to have a Toeplitz structure. In this paper, we analyze this method, by considering the asymptotic regime where $M,N$ both converge to infinity at the same rate, and by studying consistency and asymptotic normality of the related DoA estimates.