Sampling patterns for off-the-grid spectral estimation

Maxime Ferreira Da Costa and Wei Dai

51st Asilomar Conference on Signals, Systems, and Computers, 2017.

Abstract

Recent results have shown that it is possible to recover signals having sparse line spectra from few temporal observations via the use of convex programming. However, the computational cost of such approaches remains the major flaw to their use in practical system. We propose a highly scalable algorithm relying on partial observation of the signal in the time domain. A deterministic sub-sampling pattern is introduced and its benefit on the computational complexity of the recovery are highlighted. Moreover, specific sub-Nyquist recovery guarantees are derived for this pattern.

Cite

@inproceedings{Ferreira2017Sampling,
  author    = {Ferreira Da Costa, Maxime and Dai, Wei},
  title     = {Sampling patterns for off-the-grid spectral estimation},
  booktitle = {2017 51st Asilomar Conference on Signals, Systems, and Computers},
  pages     = {318-322},
  year      = {2017},
  doi       = {10.1109/ACSSC.2017.8335192}
}