HiFAST: An HI Data Calibration and Imaging Pipeline for FAST III. Standing Wave Removal

TL;DR

This paper introduces the HiFAST pipeline with an FFT filter method to effectively remove standing waves and harmonic RFI from FAST radio telescope data, improving spectrum quality and calibration efficiency.

Contribution

The paper presents a novel FFT filter approach integrated into the FAST data pipeline, significantly reducing standing wave effects and detecting harmonic RFI more effectively than previous methods.

Findings

FFT filter reduces RMS from 3.2 to 1.15 times the theoretical estimate

Achieves median RMS of approximately 1.2 times the theoretical expectation

Identifies three types of harmonic RFI with amplitudes over 100 mK

Abstract

The standing waves existed in radio telescope data are primarily due to reflections among the instruments, which significantly impact the spectrum quality of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Eliminating these standing waves for FAST is challenging given the constant changes in their phases and amplitudes. Over a ten-second period, the phases shift by 18$^{\circ}$ while the amplitudes fluctuate by 6 mK. Thus, we developed the fast Fourier transform (FFT) filter method to eliminate these standing waves for every individual spectrum. The FFT filter can decrease the root mean square (RMS) from 3.2 to 1.15 times the theoretical estimate. Compared to other methods such as sine fitting and running median, the FFT filter achieves a median RMS of approximately 1.2 times the theoretical expectation and the smallest scatter at 12%. Additionally, the FFT filter method avoids the flux loss issue encountered with some other methods. The FFT is also efficient in detecting harmonic radio frequency interference (RFI). In the FAST data, we identified three distinct types of harmonic RFI, each with amplitudes exceeding 100 mK and intrinsic frequency periods of 8.1, 0.5, and 0.37 MHz, respectively. The FFT filter, proven as the most effective method, is integrated into the HI data calibration and imaging pipeline for FAST (HiFAST, https://hifast.readthedocs.io).