Efficient Photometry

ABSTRACT: Current photometric calibration techniques take away too much time from performing actual collections of interest, which decreases the efficiency and usefulness of important SSA resources. In response to the AF141-013 SBIR Solicitation for Efficient Photometry, the ADS-PDS team proposes to study in-frame photometric calibration feasibility and to provide an approach that is implementable for current operations. We plan to leverage existing in-frame astrometric and photometric algorithms and software previously developed by PDS. Under this Phase I effort, ADS will add in-frame photometric calibration techniques. Furthermore, the ADS team will study the algorithm"s calibration accuracies and applicability to a diverse set of sensor field-of-views (FOVs) and signal-to-noise ratios, while validating and testing the software with actual astronomy images to ensure that it is low cost, globally applicable, near-real-time, and requires no additional collection time. We plan to pair the software with the latest, most robust photometric catalog currently available, the SST-RC3 catalog, to maximize the potential to identify stars in even the smallest FOVs. Furthermore, we will optimize the software for robustness, usability, and efficiency. The effort will conclude with a demonstration of the algorithm on standard computing hardware. BENEFIT: The ADS team"s proposed solution is expected to provide photometric calibrations of 10% or better using in-frame techniques with no a priori calibration collections, even for non-photometric sky collection nights (such as nights with dynamic photometric properties, e.g. clouds, water vapor extinction, light pollution, etc.). Since the approach works for a wide range of sensor FOVs and signal-to-noise ratios and requires no special hardware, the approach should be easily applicable to a wide range of currently operational optical SSA sensors, ranging from Raven-class telescopes to SST, and even SBSS. The approach can be shown to be beneficial even for clear filtered sensors.