Compressive recovery of 2-D off-grid frequencies

Yuejie Chi, Yuxin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations


Estimation of two-dimensional frequencies arises in many applications such as radar, inverse scattering, and wireless communications. In this paper, we consider retrieving continuous-valued two-dimensional frequencies in a mixture of r complex sinusoids from a random subset of its n regularly-spaced timedomain samples. We formulate an atomic norm minimization program that, with high probability, guarantees perfect recovery from O(r log r log n) samples under a mild frequency separation condition. We propose to solve the atomic norm minimization via semidefinite programming, and validate the proposed algorithm via numerical examples. Our work extends the framework proposed by Tang et. al. [1] for line spectrum estimation to multidimensional spectrum estimation.

Original languageEnglish (US)
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Number of pages5
ISBN (Print)9781479923908
StatePublished - 2013
Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 3 2013Nov 6 2013

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393


Other2013 47th Asilomar Conference on Signals, Systems and Computers
Country/TerritoryUnited States
CityPacific Grove, CA

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications


  • atomic norm
  • basis mismatch
  • continuous-valued frequency recovery
  • nonparametric
  • sparsity


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