New method for subtraction of common background fluctuation for radio camera: Chunked Principal Component Analysis method

We present a new algorithm, ChunkedPCA, to remove common background fluctuations from datasets acquired with a radio camera. ChunkedPCA is an improvement on using PCA to achieve fewer artifacts and better RMS on the cleaned dataset. The proposed algorithm determines the background fluctuation by grouping the detector pixels not used in the direct observation of the source. This group is then used to get the background fluctuation for that time and used to subtract the background from the data of all pixels. We apply ChunkedPCA for the numerical simulation data and a real observation data obtained with the MKID camera on the Nobeyama 45-m telescope to verify the effectiveness of the ChunkedPCA. We confirm that using the ChunkedPCA method preserves the flux of the astronomical sources and produces a cleaner baseline than the conventional PCA method.