SIMBAD references

We present and compare several methods to mitigate time-correlated (1/f) noise within the H I intensity mapping component of the MeerKAT Large Area Synoptic Survey (MeerKLASS). By simulating scan strategies, the H I signal, foreground emissions, white and correlated noise, we assess the ability of various data-processing pipelines to recover the power spectrum of H I brightness temperature fluctuations. We use MeerKAT pilot data to assess the level of 1/f noise expected for the MeerKLASS survey and use these measurements to create realistic levels of time-correlated noise for our simulations. We find the time-correlated noise component within the pilot data to be between 10 and 20 times higher than the white noise level at the scale of $k = 0.04 \, {\rm {Mpc}}^{-1}$. Having determined that the MeerKAT 1/f noise is partially correlated across all the frequency channels, we employ Singular Value Decomposition (SVD) as a technique to remove both the 1/f noise and Galactic foregrounds but find that over-cleaning results in the removal of H I power at large (angular and radial) scales; a power loss of 40 per cent is seen for a 3-mode SVD clean at the scale of $k = 0.04 \, {\rm {Mpc}}^{-1}$. We compare the impact of map-making using weighting by the full noise covariance (i.e. including a 1/f component), as opposed to just a simple unweighted binning, finding that including the time-correlated noise information reduces the excess power added by 1/f noise by up to 30 per cent.