Super-resolution Line Spectrum Estimation with Block Priors
arXiv:1404.7041
Abstract
We address the problem of super-resolution line spectrum estimation of an undersampled signal with block prior information. The component frequencies of the signal are assumed to take arbitrary continuous values in known frequency blocks. We formulate a general semidefinite program to recover these continuous-valued frequencies using theories of positive trigonometric polynomials. The proposed semidefinite program achieves super-resolution frequency recovery by taking advantage of known structures of frequency blocks. Numerical experiments show great performance enhancements using our method.
arXiv comment7 pages, double column
References in corpus (6)
- From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals
- Structured Compressed Sensing: From Theory to Applications
- Modified-CS: Modifying Compressive Sensing for Problems with Partially Known Support
- Line Spectrum Estimation with Probabilistic Priors
- Off-The-Grid Spectral Compressed Sensing With Prior Information
- Spike detection from inaccurate samplings