Clustered Radio Interferometric Calibration

TL;DR

This paper proposes a clustered calibration method for radio interferometry that improves calibration accuracy for weak sources by leveraging information from stronger sources within the same cluster, demonstrating superior performance over traditional methods.

Contribution

It introduces a novel clustered calibration approach that groups sources and calibrates them collectively, enhancing calibration for sources below the noise level.

Findings

Clustered calibration outperforms un-clustered methods in accuracy.

Using source clusters reduces calibration errors for weak signals.

The method is effective in practical radio interferometric scenarios.

Abstract

This paper introduces an amendment to radio interferometric calibration of sources below the noise level. The main idea is to employ the information of the stronger sources' measured signals as a plug-in criterion to solve for the weaker ones. For this purpose, we construct a number of source clusters, with centroids mainly near the strongest sources, assuming that the signals of the sources belonging to a single cluster are corrupted by almost the same errors. Due to this characteristic of clusters, each cluster is calibrated as a single source, using all the coherencies of its sources simultaneously. The obtained solutions for every cluster are assigned to all the cluster's sources. An illustrative example reveals the superiority of this calibration compared to the un-clustered calibration.