Optimizing point-source parameters for scanning satellite surveys

TL;DR

This paper presents a novel iterative method for accurately deriving point-source positions and fluxes from scanning satellite data, significantly improving over traditional pixel map analysis by utilizing the original scan data and detailed beam profiles.

Contribution

The paper introduces a new iterative approach that leverages original scan data and beam profiles to enhance point-source parameter estimation in satellite surveys.

Findings

Achieves at least 10-fold improvement over pixel map extraction.

Effectively combines multi-frequency positional data for better flux accuracy.

Includes potential for geometric calibration correction.

Abstract

We describe a method for deriving the position and flux of point and compact sources observed by a scanning survey mission. Results from data simulated to test our method are presented, which demonstrate that at least a 10-fold improvement is achievable over that of extracting the image parameters, position and flux, from the equivalent data in the form of pixel maps. Our method achieves this improvement by analysing the original scan data and performing a combined, iterative solution for the image parameters. This approach allows for a full and detailed account of the point-spread function, or beam profile, of the instrument. Additionally, the positional information from different frequency channels may be combined to provide the flux-detection accuracy at each frequency for the same sky position. Ultimately, a final check and correction of the geometric calibration of the instrument may also be included. The {\it Planck} mission was used as the basis for our simulations, but our method will be beneficial for most scanning satellite missions, especially those with non-circularly symmetric point-spread functions.