Adaptive Calibration Of Radio Interferometer Data

Radio interferometer observations are, essentially, samples of V, the Fourier transform of the radio brightness, I, on a patch of sky. The dominant errors usually are ascribable to individual elements of the array. Most damaging, often, are phase errors due to atmospheric refraction, but amplitude errors also may be serious. The sampling distribution improves as an observing run progresses since, as the earth rotates, any pair of elements samples V at different spatial frequencies lying along a curve. Adaptive calibration can be achieved as follows: Assumptions on the analytic properties of I lead to a measure of the consistency of the observations, from a given instant, with the total set of data; given an appropriate error model, an overdetermined system of equations in the unknown errors results; correcting the data accordingly, an improved estimate of I is derived; and the procedure may be repeated. This encompasses schemes proposed by Readhead and Wilkinson, and by Cotton, for compensation of phase errors in very-long-baseline interferometry (VLBI); similar methods are proposed by Muller and Buffington for optical telescopes. Results in analysis of Very Large Array (VLA) data are extremely encouraging. The computational expense is a few times that of standard methods.