Efficient Photometry from Serendipitous Detection of Stars

ABSTRACT: Research Objectives: 1) Determine the viability and accuracy of photometric calibration of Resident Space Object (RSO) observations using light from stars serendipitously recorded in the RSO images across the full range of ground-based image data collection scenarios in EO/IR wavebands. 2) Develop and deliver a beta-level software code to perform automatic photometric calibration in this way, by reference to comprehensive public-domain star catalogs. Technical Approach: Using a substantially modified Hough transform algorithm, identify candidate star streaks in images of RSOs. Qualify candidate star detections against star positions in available catalogs. Establish photometric references from information in the same catalogs, and apply to the RSO images. BENEFIT: Anticipated Impact and Outcome: The proposed algorithm will greatly reduce the telescope time necessary to provide photometric calibration of RSOs, thereby significantly increasing the operational efficiency of ground-based government assets tasked with Space Situational Awareness. The code developed under this program will also be of interest to commercial and other government entities engaged in similar tasks, as well as astronomical programs devoted to the detection and characterization of natural Near Earth Objects.