A High-resolution Multi-snapshot Newtonized Orthogonal Matching Pursuit for Line Spectrum Estimation with Random Compressed Multiple Measurement Vectors

A new high-resolution multi-snapshot Newtonized orthogonal matching pursuit (MNOMP) algorithm is proposed to deal with the line spectrum estimation after random compression (RC-MNOMP) with multiple measurement vectors (MMVs) in this paper. RC-MNOMP has the low computation complexity and state-of-the-art estimation performance. Detecting a new sinusoid on an oversampled discrete Fourier transform (DFT) grid and refining the parameters of already detected sinusoids are two key steps of RC-MNOMP. A stopping criterion based on the overestimating probability of the model order is provided. Finally, numerical results are conducted to show the effectiveness and accuracy of RC-MNOMP.