Improved space object detection via scintillated short exposure image data

Abstract

Since telescopes were first trained on the heavens, nearly every attempt to locate new objects in the sky has been accomplished using long-exposure images (images taken with exposures longer than one second). For many decades astronomers have utilized short-exposure images to achieve high spatial resolution and mitigate the effect of Earth’s atmosphere. This is due to the fact that short-exposure images contain higher spatial frequency content than their long exposure counterparts. New objects, such as dim companions of binary stars have been revealed using these techniques, thus achieving some discoveries via short-exposure images, but always in context of a detailed analysis of a specific area of the sky, not through a synoptic search of the heavens like the kind carried out by asteroid research programs like Space Watch, PAN-STARRS or the Catalina Sky Survey. In this paper simulated short-exposure images are processed to detect simulated stars in the presence of strong atmospheric turbulence. The strong turbulence condition produces long-exposures with wide star patterns, while the short-exposure images feature better concentration of the available photons, but large random position variance. A new processing strategy involving a matched-filter technique using a short-exposure atmospheric impulse response model is utilized. The results from this process are compared to efforts to detect stars in long exposure images taken over the same interval the short-exposure images are collected. The two techniques are compared and the short-exposure imaging technique is found to produce the higher probability of detection.