A Sparse Reconstruction Algorithm for Multi-Frequency Radio Images

In radio interferometry, every pair of antennas in an array defines one sampling point in the Fourier domain of the sky image. By combining infor-
mation from different wavelengths, sample coverage—and therefore reconstruction quality—can be increased. However, the images at different wavelengths can be dramatically dissimilar; this fact must be taken into account when reconstructing multi-frequency images. In this paper, we present a novel reconstruction algorithm based on the assumption that the spectrum is continuous. In contrast to prior work, we allow for sparse deviations from this assumption: this allows, for example, for accurate reconstruction of line spectra superimposed on a continuum. Using simulated measurements on synthetic multi-frequency images, we show that the proposed approach provides significant improvements over a comparable method based solely on a continuity assumption.
Author(s): | Stephan Wenger, Marcus Magnor |
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Published: | November 2014 |
Type: | Technical Report |
Institution: | Inst. f. Computergraphik, TU Braunschweig |
Project(s): | Radio Astronomy Synthesis Imaging |
@techreport{wenger2014sparse, title = {A Sparse Reconstruction Algorithm for Multi-Frequency Radio Images}, author = {Wenger, Stephan and Magnor, Marcus}, institution = {Inst. f. Computergraphik, {TU} Braunschweig}, number = {20}, month = {Nov}, year = {2014} }
Authors
Stephan Wenger
Fmr. Senior ResearcherMarcus Magnor
Director, Chair