Efficient least-squares basket-weaving
1 Max-Planck-Institut für Radioastronomie (MPIfR), Auf dem Hügel 69, 53121 Bonn, Germany
2 Argelander-Institut für Astronomie (AIfA), Auf dem Hügel 71, 53121 Bonn, Germany
Received: 29 August 2012
Accepted: 10 October 2012
We report on a novel method to solve the basket-weaving problem. Basket-weaving is a technique that is used to remove scan-line patterns from single-dish radio maps. The new approach applies linear least-squares and works on gridded maps from arbitrarily sampled data, which greatly improves computational efficiency and robustness. It also allows masking of bad data, which is useful for cases where radio frequency interference is present in the data. We evaluate the algorithms using simulations and real data obtained with the Effelsberg 100-m telescope.
Key words: techniques: image processing / methods: observational
© ESO, 2012