TABASCAL II: Removing Multi-Satellite Interference from Point-Source Radio Astronomy Observations

TL;DR

TABASCAL II introduces a method to accurately remove multi-satellite RFI from radio interferometry data, enabling near-perfect imaging quality comparable to RFI-free observations, even with strong interference.

Contribution

It presents a novel RFI removal technique that effectively isolates and subtracts multiple satellite signals, preserving astronomical data quality in simulated MeerKAT observations.

Findings

TABASCAL achieves near-perfect RFI removal across all satellite strengths.

It maintains high image quality comparable to no-RFI data.

Outperforms existing flagging methods like AOFlagger in strong RFI conditions.

Abstract

In the first TABASCAL paper we showed how to calibrate in the presence of Radio Frequency Interference (RFI) sources by simultaneously isolating the trajectories and signals of the RFI sources. Here we show that we can accurately remove RFI from simulated MeerKAT radio interferometry target data, for a single frequency channel, corrupted by up to 9 simultaneous satellites with average RFI amplitudes varying from weak to very strong (1 - 1000 Jy). Additionally, TABASCAL also manages to leverage the RFI signal-to-noise to phase calibrate the recovered astronomical signal. TABASCAL effectively performs a suitably phased up fringe filter for each RFI source which allows essentially perfect removal of RFI across all strengths. As a result, TABASCAL reaches image noises equivalent to the uncorrupted, no-RFI, case. Consequently, point-source science with TABASCAL almost matches the no-RFI case with near perfect completeness for all RFI amplitudes. In contrast the completeness of AOFlagger and idealised 3$\sigma$ flagging drops below 40% for strong RFI amplitudes where recovered flux errors are $\sim$10x-100x worse than those from TABASCAL. Finally we highlight that TABASCAL works for both static and varying astronomical sources.