MUSIC for Single-Snapshot Spectral Estimation
نویسندگان
چکیده
Single-snapshot line spectral estimation is carried out with one compressed sensing technique, Band-excluding Locally Optimized Orthogonal Matching Pursuit (BLOOMP), and two subspace-based methods, Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT). Simulations show that for separation greater than 3 RL, BLOOMP is the best performer while for separation between 2 to 3 RL, ESPRIT and MUSIC are the equally best performers. ESPRIT is by far the computationally most efficient, followed by MUSIC and BLOOMP.
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