Parametric high resolution techniques for radio astronomical imaging

Chen Ben-David*, Amir Leshem

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The increased sensitivity of future radio telescopes will result in requirements for higher dynamic range within the image as well as better resolution and immunity to interference. In this paper, we propose a new matrix formulation of the imaging equation in the cases of non-co-planar arrays and polarimetric measurements. Then, we improve our parametric imaging techniques in terms of resolution and estimation accuracy. This is done by enhancing both the minimum variance distortionless response (MVDR) parametric imaging, introducing alternative dirty images, and by introducing better power estimates based on least squares, with positive semi-definite constraints. We also discuss the use of robust Capon beamforming and semi-definite programming for solving the self-calibration problem. Additionally, we provide statistical analysis of the bias of the MVDR beamformer for the case of moving array, which serves as a first step in analyzing iterative approaches such as CLEAN and the techniques proposed in this paper. Finally we demonstrate a full deconvolution process based on the parametric imaging techniques and show its improved resolution and sensitivity compared to the CLEAN method.

Original languageAmerican English
Pages (from-to)670-684
Number of pages15
JournalIEEE Journal on Selected Topics in Signal Processing
Volume2
Issue number5
DOIs
StatePublished - 2008
Externally publishedYes

Keywords

  • CLEAN
  • Convex optimization
  • Minimum variance
  • Parametric imaging
  • Radio astronomy
  • Robust beamforming
  • Synthesis imaging

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