DocumentCode :
1177385
Title :
Imaging gamma-ray sources with a Compton Double Scatter telescope using the Expectation Maximization Maximum Likelihood (EMML) technique
Author :
Sarmouk, A. ; Zych, A.D. ; O´Neill, T. ; White, R.S. ; Tumer, O.T.
Author_Institution :
Inst. of Geophys. & Planetary Phys., California Univ., Riverside, CA, USA
Volume :
41
Issue :
4
fYear :
1994
fDate :
8/1/1994 12:00:00 AM
Firstpage :
1349
Lastpage :
1353
Abstract :
An Expectation Maximization Maximum Likelihood method (EMML) introduced by T.J. Hebert has been expanded and used to reconstruct gamma-ray source images. The specific application of this technique to Compton double scatter data is discussed in this paper. This method shows reliable results for low event counts such as from weak sources or short data acquisition times. Results for simulation and calibration data for fixed and moving sources are presented. The response function of the detector used and the background subtraction are discussed. The method is sensitive to sources with a signal-to-noise ratio of 1%. This method is being used to analyze the 1989 balloon flight data collected by the University of California, Riverside Double Scatter Compton telescope flown at Fort Sumner, New Mexico. Results from the Crab region are shown
Keywords :
Compton effect; astronomical telescopes; gamma-ray astronomy; inverse problems; maximum likelihood estimation; Compton Double Scatter telescope; Crab Nebula; EMML method; Expectation Maximization Maximum Likelihood method; background subtraction; calibration; fixed sources; gamma-ray source images; moving sources; reconstruction; response function; signal-to-noise ratio; simulation; Data acquisition; Gamma ray detection; Gamma ray detectors; Gamma rays; Image reconstruction; Maximum likelihood detection; Maximum likelihood estimation; Optical imaging; Scattering; Telescopes;
fLanguage :
English
Journal_Title :
Nuclear Science, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9499
Type :
jour
DOI :
10.1109/23.322912
Filename :
322912
Link To Document :
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