Correcting atmospheric-induced phase errors of a synthetic aperture antenna array by time series modeling and Kalman filtering.
Abstract
A new technique is discussed and developed for correcting atmospherically induced errors in phase data collected by radio astronomy interferometers and synthetic aperture antenna arrays. The main features of this technique are modeling and filtering the information content of the complex visibility data in time sequences. In conjunction with other radio astronomy data processing algorithms, a time series modeling and parameter estimation technique is developed to obtain noise models and source models from observed phase data. These models can be in the form of stochastic difference equations, autocorrelation, power spectral density, and a state space format ready for further data processing. One useful application of this technique is for reducing atmospherically induced phase errors of small synthesis arrays that have too few antennas to apply self-calibration. Another application of this technique is for improving the performance of large synthesis arrays when the standard calibration methods are insufficient for correcting very noisy phase data. This technique has been tested using VLA and the Hat Creek millimeter interferometer.
- Publication:
-
Radio Science
- Pub Date:
- December 1990
- DOI:
- 10.1029/RS025i006p01145
- Bibcode:
- 1990RaSc...25.1145Z
- Keywords:
-
- Antenna Arrays;
- Atmospheric Correction;
- Kalman Filters;
- Phase Error;
- Synthetic Aperture Radar;
- Time Series Analysis;
- Image Processing;
- Radio Astronomy;
- Radio Interferometers;
- Radio Sources (Astronomy);
- Seeing (Astronomy);
- State Estimation;
- Antennas: Radio Astronomy;
- Methods of Reduction: Radio Interferometers