Before revision:  In this work , we propose two efficient approximate algorithms to significantly accelerate the high-resolution subspace algorithm. In particular, our fast MUST algorithms speed up the expensive signal subspace identification step using the randomized low-rank approximations.
After revision:  In this work , we propose two efficient approximate algorithms to significantly accelerate the high-resolution estimation of angle of arrival (AoA) information. By leveraging randomized low-rank approximation, our fast-MUSIC approaches, relying on random sampling and projection techniques, would speed up the expensive signal subspace identification step using the randomized low-rank approximations.