New Methods for Precision Radio Imaging: Field of View Control Using Convolution Functions in the u,v Plane

Details New Methods for Precision Radio Imaging: Field of View Control Using Convolution Functions in the u,v Plane New Methods for Precision Radio Imaging: Field of View Control Using Convolution Functions in the u,v Plane

Jan 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21346708f&link_type=abstract

American Astronomical Society, AAS Meeting #213, #467.08; Bulletin of the American Astronomical Society, Vol. 41, p.415

Computer Science

Performance

Scientific paper

Future radio telescope arrays, such as the Square Kilometer Array (SKA), will implement large numbers of small diameter dishes configured over large areas. This has the advantage of a naturally large field of view (FOV), and increased image fidelity and dynamic range. However, a major problem for these large arrays is varying instrumental response to radio sources across the FOV, as well as significant responses to sources outside the intended FOV. These effects can degrade image quality and sensitivity at the primary location of interest. One approach to this problem is to apply a convolution function to the uncalibrated visibility data in the time/frequency plane on a baseline-by-baseline basis, corresponding to a convolution function of uniform size and shape in the (u,v) plane. This provides precise, dynamic control over the FOV in the image plane in an internally consistent manner throughout the (u,v) data set. The effect is to reduce the sidelobe confusion contributions from secondary sources, as well as constituting intelligent time and frequency averaging as a means of reducing data volumes. The effectiveness of this method was tested on observational data using the MERLIN array in the United Kingdom. Using an updated version of the MIT Array Performance Simulator (MAPS), a simulated data set modeling the actual data set was generated for comparison. The performance of the convolution method on an actual data set is compared against the results on the simulated data set. The robustness of the method is also investigated by simulating large portions of lost or corrupted data. The results show that the use of convolution functions on uncalibrated (u,v) data is a promising method for limiting instrumental response to sources outside a user-defined FOV. This project was supported through an NSF/REU grant at MIT Haystack Observatory.

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