Presentation + Paper
9 July 2018 Coherent integration: theory and practice
Author Affiliations +
Abstract
It has long been recognized that, in the low signal-to-noise regime, the visibility SNR is improved by co-adding frames, each rotated by an estimate of its phase. However, implementation of this technique is challenging. Where it is most needed, on low SNR baselines and when combining multiple phases to estimate the phase for a lower SNR baseline, phase errors reduce the amplitude by a large amount and in a way that has proven difficult to calibrate. In this paper, an improved coherent integration algorithm is presented. It eliminates heuristics by fitting a parameterized model for the phase as a function of time and wavelength to the entire data set. This framework is used to build a performance model which can be used in two ways. First, it can be used to test the algorithm; by comparing its performance to theory, one can test how well the parameter fitting has worked. Also, when designing future systems, this model provides a simple way to predict performance and compare it to alternative techniques such as hierarchical fringe tracking.

When bootstrapping several baselines, the noise variance is about a factor of two smaller than normally assumed. This technique has been applied to both simulated and stellar data.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. Mozurkewich and Anders Jorgensen "Coherent integration: theory and practice", Proc. SPIE 10701, Optical and Infrared Interferometry and Imaging VI, 107011N (9 July 2018); https://doi.org/10.1117/12.2311817
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KEYWORDS
Visibility

Data modeling

Calibration

Performance modeling

Signal to noise ratio

Data integration

Data processing

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