Sparse Signal Reconstruction Using Blind Super-Resolution With Arbitrary Sampling

Hoomaan Hezaveh, Milad Javadzadeh, Mohammad Hossein Kahaei

Abstract: The problem of blind super-resolution of sparse signals using arbitrary sampling and the atomic lift is studied. Using the Prolate Spheroidal Wave Functions (PSWFs) and matrix atomic norm, a new Semi-Definite Program (SDP) is proposed. Unlike the previous results, the proposed new version of SDP can localize spikes with higher precision and no need for the magnitude recovery and integer sampling schemes. Numerical simulations show that our method outperforms the recent techniques with generating a lower Normalized Mean Square Error (NMSE).