Abstract
The Radio Astronomical Survey (RAS) is a collection of image cubes that represent specific regions in the sky. They are produced through an automated Data Processing Pipeline. In this process, radio astronomical signals received from a radio telescope are mapped to image cubes. Each image cube consists of thousands of two-dimensional images, each image represents the radio signals received by the telescope at a certain frequency. The final stage of the Pipeline process is to visually inspect the produced surveys to discover artifacts. In addition to being a time consuming process, the manual inspection is subjective which makes the validation process imperfect and non-uniform. One of the common artifacts in several RASs is the Hexagonal Pattern Artifact (HPA) which may happen due to telescope influence. Since these artifacts are undesirable, they should be removed or flagged before releasing the RAS to the community. This research presents the first algorithm for Automatic Identification of HPA in RAS (AIHR). The automation process will dramatically reduce the amount of time and effort invested to manually discover HPAs.
Author
Said, D. ; Stil, J. ; Taylor, R. ; Barker, K.
Journal
Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on
Paper Publication Date
December 2013
Paper Type
Astroinformatics