Distributed Radio Interferometric Calibration

@article{Yatawatta2015DistributedRI,
  title={Distributed Radio Interferometric Calibration},
  author={Sarod Yatawatta},
  journal={ArXiv},
  year={2015},
  volume={abs/1502.00858}
}
Increasing data volumes delivered by a new generation of radio interferometers require computationally efficient and robust calibration algorithms. In this paper, we propose distributed calibration as a way of improving both computational cost as well as robustness in calibration. We exploit the data parallelism across frequency that is inherent in radio astronomical observations that are recorded as multiple channels at different frequencies. Moreover, we also exploit the smoothness of the… 

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References

SHOWING 1-10 OF 23 REFERENCES
Nonlinear Kalman filters for calibration in radio interferometry
The data produced by the new generation of interferometers are affected by a wide variety of partially unknown complex effects such as pointing errors, phased array beams, ionosphere, troposphere,
Radio Interferometric Calibration Using The SAGE Algorithm
TLDR
The Space Alternating Generalized Expectation Maximization (SAGE) calibration technique is presented, which is a modification of the Expectations Maximization algorithm, and its performance is compared with the traditional least squares calibration based on the level of solver noise introduced by each technique.
On the interpolation of calibration solutions obtained in radio interferometry
TLDR
The theory of quotient manifolds is proposed to be used for obtaining correct interpolants that are immune to unitary matrix ambiguities and the case where each solution is affected by any unknownunitary ambiguity is presented.
Reduced ambiguity calibration for LOFAR
TLDR
A method for LOFAR calibration which does not yield a unitary ambiguity, especially under ionospheric distortions is presented and cases where due to degeneracy, this method fails to perform as expected and in such cases, it is suggested exploiting diversity in time, space and frequency.
PURIFY: a new approach to radio-interferometric imaging
TLDR
The authors release a beta version of an SDMM-based imaging software written in C and dubbed PURIFY that handles various sparsity priors, including the recent average sparsity approach SARA, and evaluates the performance of different priors through simulations in the continuous visibility setting, confirming the superiority of SARA.
Interferometry and Synthesis in Radio Astronomy
Preface to the Second Edition. Preface to the First Edition. Introduction and Historical Review. Introductory Theory of Interferometry and Synthesis Imaging. Analysis of the Interferometer Response.
Interferometry And Synthesis In Radio Astronomy
TLDR
The interferometry and synthesis in radio astronomy is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
D-ADMM: A Communication-Efficient Distributed Algorithm for Separable Optimization
TLDR
D-ADMM is proven to converge when the network is bipartite or when all the functions are strongly convex, although in practice, convergence is observed even when these conditions are not met.
Multi-Agent Distributed Optimization via Inexact Consensus ADMM
TLDR
Low-complexity algorithms are proposed that can reduce the overall computational cost of consensus ADMM by an order of magnitude for certain large-scale problems and offer considerably lower computational complexity.
A Distributed and Scalable Processing Method Based Upon ADMM
  • T. Erseghe
  • Computer Science
    IEEE Signal Processing Letters
  • 2012
TLDR
This letter proposes a modification of state-of-the-art ADMM formulations in order to obtain a scalable version, well suited for a wide range of applications such as cooperative localization and smart grid optimizations.
...
...