Poster + Presentation + Paper
13 December 2020 A detection algorithm for faint sources based on 1-d projection for a lobster-eye x-ray imaging system
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Conference Poster
Abstract
We propose an optimized source detection algorithm with an X-ray wide-field imaging detector based on lobstereye (LE) optics to realize better sensitivity. In our method, we take two parts of region of interest (ROI) in which we test the number of X-ray events exceed a certain threshold level. Since we compose the condition that the excesses of the photons are required for the both parts of the ROI, we can lower the detection threshold level with a less false alert rate. We take two comparative methods in which the ROI consists of one part, and compared the performance of them. We formulated an appropriate threshold level and sensitivity for two comparable detection methods as well as our proposed method. We found that the detection sensitivity of our method is improved by a factor of about 30% at most than that of the comparable methods in the nominal case of the proposed HiZ-GUNDAM mission. We also found that which detection method has better sensitivity depends on the background event rate. We checked that the formulation works well by comparing to a Monte Carlo simulation in the case of the HiZ-GUNDAM condition. The formula can be applied to any future missions with LE optics to design which detection algorithm is suitable for optimizing sensitivity.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tatsuya Sawano, Daisuke Yonetoku, Makoto Arimoto, Jin Li, Tatehiro Mihara, Naoki Ogino, Takanori Sakamoto, and Motoko Serino "A detection algorithm for faint sources based on 1-d projection for a lobster-eye x-ray imaging system", Proc. SPIE 11444, Space Telescopes and Instrumentation 2020: Ultraviolet to Gamma Ray, 114445K (13 December 2020); https://doi.org/10.1117/12.2560604
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KEYWORDS
X-ray imaging

Imaging systems

Detection and tracking algorithms

Photons

Signal to noise ratio

Point spread functions

Astronomy

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