Parametric high resolution techniques for radio astronomical imaging

TL;DR

This paper introduces advanced parametric imaging techniques for radio astronomy that enhance resolution, accuracy, and robustness, addressing challenges posed by future high-sensitivity telescopes and complex array configurations.

Contribution

It develops a new matrix formulation for imaging equations, improves MVDR and power estimation methods, and integrates robust beamforming and semi-definite programming for better imaging and calibration.

Findings

Enhanced resolution and sensitivity over traditional methods

Effective self-calibration using semi-definite programming

Statistical analysis of beamformer bias for moving arrays

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 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.