RFI Mitigation in AIPS. The New Task UVRFI
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March 2010 RFI 2010 RFI Mitigation in AIPS. The New Task UVRFI L. Kogan, F. Owen National Radio AstronomyObservatory Socorro, NM USA
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RFI Mitigation in AIPS. The New Task UVRFI. L. Kogan, F. Owen National Radio AstronomyObservatory Socorro, NM USA. Visibility expression in the setting of RFIs moving with constant velocities relatively the array. - PowerPoint PPT Presentation
Transcript of RFI Mitigation in AIPS. The New Task UVRFI
March 2010 RFI 2010
RFI Mitigation in AIPS.The New Task UVRFI
L. Kogan, F. OwenNational Radio AstronomyObservatory
Socorro, NM USA
Visibility expression in the setting of RFIs moving with constant velocities relatively the array
Given correlator outputs during the solution interval and considering the all RFI amplitudes are constant within of the solution interval, our goal is to find the value of the source visibility for the solution interval!
March 2010 RFI 2010
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The Athreya’s approach to the problem: The circular model
Ramana Athreya, APJ, 696, 885-890, May 2009
Consider RFI which includes one group moving with constant velocity (in particular located at the Earth or one satellite). Assuming constant amplitude inside of the solution interval, the trajectory of the correlator output in the complex plane is the circle with radius equal to RFI amplitude. The center coordinates are Re, Im of the source visibility.
Fitting the 3 parameters: radius of the circle, and the two coordinates of the circle center, the aquired coordinates of the circle center are the solution for the source visibility without RFI
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The visibility spectrum for one baseline of Rupen’s data (L band)
One of the best “circle”
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The new AIPS task UVRFIUVRFI uses the 2 algorithms: 1. ‘CIRC’ a l’a Athrea The spiral with 4 unknown parameters: initial radius, linear increment of the radius, 2 coordinates of the center is fitted to the data. The 2 coordinates of the center are used as a solution for the free RFI visibility.
2. ‘CEXP’ The model is represented by the sum of several spectral components with complex amplitude.
The simple version of the Hogbom clean algorithm (complex Fourier transform, complex solution and complex “PSF”) is used to subtract the the complex components.
Final solution is the value of the cleaned Fourier transform at zero frequency.
The subtraction is not carried out for the component at zero frequency to prevent the subtraction of the signal itself. This rule is canceled for the very high channel amplitude in comparison with other channels.
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The actual shape of the “circles”. L-band data (given by M. Rupen).
The visibility spectrum for one baseline of Rupen’s data (L band)
The averaged output The UVRFI output
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The image of 3C345 using Rupen’s data (L band)
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The averaged output The UVRFI outputThe averaged output The UVRFI output
The actual shape of the “circles”. 4-band data (given by B. Cotton).
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The visibility spectrum for one baseline of Cotton’s data (4 band)
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The averaged output The UVRFI outputThe averaged output The UVRFI output
The images using the Cotton’s data (4 band)
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The averaged output The UVRFI outputThe averaged output The UVRFI output
Self averaging of the visibilities in the process of imaging
Therefore the effect of self averaging of RFI may not limited by the correlator averaging interval (as Athrea declares) but rather by the time interval where both U and V can be considered constant!
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ConclusionsThe new AIPS task UVRFI uses the two algorithms to mitigate RFI.
• CIRC function based on modification of Ramana Athrea algorithm fits a spiral into the observed visibility curve in the complex plane
• CEXP function subtracts the complex exponents representing RFI, using a simple CLEAN algorithm at the Fourier plane
•The second algorithm demonstrates better result for the two data I used and allows to mitigate more than one sources of RFI (ground, satellites)
•The utility of RFI mitigation algorithms is complicated by the non-circular nature of the RFI in the sample datasets.
•In some cases, RFI may be self averaged during imaging
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