Radio Frequency Interference Mitigation and Statistics in the Spectral Observations of FAST

In radio astronomy, radio frequency interference (RFI) becomes more and more serious for radio observational facilities. The RFI always influences the search and study of the interesting astronomical objects. Mitigating the RFI becomes an essential procedure in any survey data processing. Five-hundred-meter Aperture Spherical radio Telescope (FAST) is an extremely sensitive radio telescope. It is necessary to find out an effective and precise RFI mitigation method for FAST data processing. In this work, we introduce a method to mitigate the RFI in FAST spectral observation and make a statistics for the RFI using ∼300 hours FAST data. The details are as follows. Firstly, according to the characteristics of FAST spectra, we propose to use the ArPLS algorithm for baseline fitting. Our test results show that it has a good performance. Secondly, we flag the RFI with four strategies, which are to flag extremely strong RFI, flag long-lasting RFI, flag polarized RFI, and flag beam-combined RFI, respectively. The test results show that all the RFI above a preset threshold could be flagged. Thirdly, we make a statistics for the probabilities of polarized XX and YY RFI in FAST observations. The statistical results could tell us which frequencies are relatively quiescent. With such statistical data, we are able to avoid using such frequencies in our spectral observations. Finally, based on the ∼300 hours FAST data, we got an RFI table, which is the most complete database currently for FAST.

Adaptive Baseline Fitting for 1H MR Spectroscopy Analysis

PurposeAccurate baseline modeling is essential for reliable MRS analysis and interpretation — particularly at short echo-times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study a new method is presented to estimate its optimal value.MethodsAn adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency-domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a four stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI — both at a field strength of 3 Tesla.ResultsSimulated analyses demonstrate metabolite errors result from two main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (over-fitting). In the case of an ideal flat baseline ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue.ConclusionABfit has been shown to perform accurate baseline estimation and is suitable for fully-automated routine MRS analysis.

Baseline Correction of Digital Accelerograms from Field Testing of a Seismically Isolated Building

A three-story reinforced-concrete building in Augusta, Sicily, isolated at the base and designed according to the provisions of the latest Italian seismic regulations, was subjected to a series of push and sudden release tests in March 2013. During the tests, the displacements at the isolation level were measured along with the accelerations at each floor. The obtained records were then treated for the removal of low-frequency noise using a simple baseline-fitting scheme. The developed signal-processing scheme consists of defining the duration of the main event, removing the background noise, and using polynomial curves for the adjustment of the distorted baseline. The method does not require significant computational effort and accounts for initial and end conditions provided that these are known. Implementation of the method provides the adjusted response in terms of absolute and relative floor accelerations, velocities, and displacements, as well as interstory drifts.