Statistics – Computation
Scientific paper
Dec 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsh44a..07b&link_type=abstract
American Geophysical Union, Fall Meeting 2006, abstract #SH44A-07
Statistics
Computation
0540 Image Processing, 0933 Remote Sensing, 3260 Inverse Theory, 6982 Tomography And Imaging (7270, 8180), 7509 Corona
Scientific paper
The combination of the soon to be launched STEREO mission with SOHO will provide scientists with three simultaneous space-borne views of the Sun. The increase in available measurements will reduce the data acquisition time necessary to obtain 3D coronal electron density (N_e) estimates from coronagraph images using a technique called solar rotational tomography (SRT). However, the data acquisition period will still be long enough for the corona to dynamically evolve, requiring time dependent solar tomography. The Kalman filter (KF) would seem to be an ideal computational method for time dependent SRT. Unfortunately, the KF scales poorly with problem size and is, as a result, inapplicable. A Monte Carlo approximation to the KF called the localized ensemble Kalman filter was developed for massive applications and has the promise of making the time dependent estimation of the 3D coronal N_e possible. We present simulations showing that this method will make time dependent tomography in three spatial dimensions computationally feasible.
Butala M. D.
Frazin Richard A.
Kamalabadi Farzad
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