Comparing Detection Algorithms for Detecting Near-Earth Objects

Astronomy and Astrophysics – Astronomy

Scientific paper

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Scientific paper

As part of developing automatic detection software for the Catalina Sky Survey, we have been investigating the operational efficiency of list-based algorithms utilizing 3, 4 and 5 images of the same field at different times and of a 5 image average minus median method of eliminating background stars for our large (2.5 arcsec) pixel data. We have investigated the relative detection efficiency of moving objects with these methods as a function of background star density and solar elongation for detections of objects at various levels above background noise that produce an acceptably small number of false positive detections. Results and their application will be presented. This work is supported by NASA NEO Observations grant NAGW58015

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