Abstract
Having an accurate calibration method is crucial for any scientific research done by a radio telescope. The next generation radio telescopes such as the Square Kilometre Array (SKA) will have a large number of receivers which will produce exabytes of data per day. In this paper we propose new direction-dependent and independent calibration algorithms that, while requiring much less storage during calibration, converge very fast. The calibration problem can be formulated as a non-linear least square optimization problem. We show that combining a block-LDU decomposition with Gauss-Newton iterations produces systems of equations with convergent matrices. This allows significant reduction in complexity per iteration and very fast converging algorithms. We also discuss extensions to direction-dependent calibration. The proposed algorithms are evaluated using simulations.
| Original language | English |
|---|---|
| Title of host publication | 2018 26th European Signal Processing Conference (EUSIPCO) |
| Publisher | IEEE |
| Pages | 2688-2692 |
| Number of pages | 5 |
| ISBN (Electronic) | 978-9-0827-9701-5 |
| ISBN (Print) | 978-1-5386-3736-4 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | EUSIPCO 2018: 26th European Signal Processing Conference - Rome, Italy Duration: 3 Sept 2018 → 7 Sept 2018 Conference number: 26 |
Conference
| Conference | EUSIPCO 2018 |
|---|---|
| Country/Territory | Italy |
| City | Rome |
| Period | 3/09/18 → 7/09/18 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Keywords
- Calibration
- Covariance Matching
- Non-Linear Optimization
- Radio Astronomy