by Qingguo Zeng, Xue Chen, Xiangru Li, J. L. Han, Chen Wang, D. J. Zhou, Tao Wang
The proposed RFI mitigation method utilizes Asymmetrically Reweighted Penalized Least Squares algorithm (ArPLS) and SumThreshold (ST), referred to as ArPLS-ST. ArPLS is used to estimate the baseline of the time-frequency image. After baseline removal, the pixel intensity in the time-frequency image should be almost constant in the interference-free regions. Meanwhile, the RFI regions still remain much higher intensity. Then, SumThreshold is performred on the time-integral curve/Spectral Energy Distribution (SED) curve and time-frequency image to detect band RFI and blob RFI (a short and small-bandwidth interference typically covering nearly 100 microseconds and bandwidth of less than one MHz).
baseline.pyincludes ArPLS and Gaussian filter;
In this code, you can run our methods on fits file. The main program detect the RFI in the time-frequency image utilizing ArPLS-ST and SumThrehold , respectively.
The program will output three images as follow:
If you find ArPLS-ST useful in your research, please citing:
Zeng et al. 2021, MNRAS Vol.500, p.2969,
with bib entry here .
 SEEKcontact: firstname.lastname@example.org