Advanced Radio Imaging Techniques

Transcription

1 Advanced Radio Imaging Techniques Dylan Nelson August 10, 2006 MIT Haystack Observatory Mentors: Colin Lonsdale, Roger Cappallo, Shep Doeleman, Divya Oberoi

2 Overview Background to the problem Data volumes in next-generation radio telescopes Our approach FOV Weighting Concept, Implementation, Results RFI excision Concept Required development Results Further investigation

3 LNSD & Data Volume Next-generation radio telescope arrays USSKA Proposal Naturally wide fields of view Science objectives High sensitivity requirements Removal of sidelobe responses from off-center sources traditionally requires post-correlation data processing Estimates of data rates ~ petabytes/sec Need a way to restrict the field of view

4 Correlator Field of View (u,v)) plane FT image plane Fourier transform relationship between the (u,v( u,v) plane and the image/sky plane Convolving the (u,v( u,v) ) plane by a windowing function Multiplying the sky by its Fourier transform Restricted FOV is imposed on data before it exits the correlator

5 FOV Weighting - Concept Windowing function is applied in the (u,v( u,v) plane, with a corresponding representation in the (t,f( t,f) ) plane (u,v)) Plane (t,f)) Plane v f f 2 FOV convolution function t 1 t 2 f 1 u t

6 FOV Weighting - Concept Various families of convolution functions have different characteristics: Tophat windowing (unit step) function Gaussian weighting function Prolate spheriodal wave functions Amplitude attenuation rate (falloff) vs. extended ripple structure

7 FOV Weighting - Concept Tophat (unit step) function 1D 2D Step Function 1 1D 2D Sinc Jinc Function

8 MAPS Simulator Flow Simulation array imaging_spec obs_spec sky site visgen injection point for FOV weighting conversions.fits output imaging and analysis

9 FOV Weighting - Implementation (u ref,v ref ) (u,v) (u,v)) patch For each baseline, an integration is performed to create a visibility point For each point integrated over, weight appropriately to enforce the windowing function

10 FOV Weighting - Method Behavior tested on a plus-configuration generated sky Sources placed at known locations should reflect falloff as a function of distance from the phase center Source intensities should, hopefully, correspond to the Fourier transform of the window function

11 FOV Weighting - Results

12 Unanswered Questions Limit to baseline length dynamic range Calibration tolerance requirements Effects of missing (t,f)) data Level of (t,f( t,f) resolution/subdivision required Required amount of source suppression as a function of radius Simulated skies vs. benchmark realistic skies Computational feasibility for actual implementation in a correlator

13 RFI Excision - Concept Data gaps in (t,f( t,f) ) domain Automated RFI excision pre-correlation Narrow band vs. wide band RFI Excision in (t,f( t,f) ) plane is uniform for all baselines Differ on a baseline per baseline basis on the (u,v( u,v) ) plane Result: FOV weighting functions are non-uniform among baselines f f 2 v 1 st Baseline t 1 t 2 f 1 nd Baseline 2 nd t u

14 RFI Excision - Method v (u,v)) Plane t f u In order to implement a uniform size (u,v)) convolution function, larger (u,v)) patches must be subdivided in next-generation correlators

15 RFI Excision - Changes

16 RFI Excision - Results Source Maximum Center RMS

17 RFI Excision - Results Source Maximum Center RMS

18 RFI Excision - Results

19 Further Investigation Field of view weighting appears promising, though more extensive testing required More extensive tests on RFI excision effects Other parameters of importance: Benchmark realistic skies Multiple array geometries Baseline length dynamic ranges Frequency/time sampling dependence Realistic calibration drift & error Different convolution functions

20 Questions?