Award

ABSTRACT:As space continues to become more congested and contested, our ability to identify and mitigate man-made and natural threats to space assets becomes increasingly difficult. The detectable population of resident space objects (RSOs) is not comprehensively quantified. Detection, tracking, and classification of objects such as cubesats, nanosatellites, and space debris that threaten military and commercial satellites is particularly challenging for geosynchronous earth orbits (GEO) and near-GEO regimes. To address the challenge of characterizing the population of artificial space objects, ExoAnalytic Solutions proposes to develop DENSE. ExoAnalytic will develop an information-driven method for designing space-based EO/IR sensors and multi-sensor architectures that will provide maximum detectability and state assessment of GEO and near-GEO space objects. Sensor design will focus on parameters of optical sensors affecting minimum detectable target (ex. aperture, quantum efficiency, detection algorithms) and data collection for feature estimation (ex. size, shape, surface material properties). Architecture design will focus on critical system performance figures of merit including maximizing detections within a specified period of time.BENEFIT:The development of DENSE will be significant for SSA because it will: - Allow for a better understanding of the space debris environment in the 1-10 cm size regime - Quantitatively compare the performance of various space-based sensor design alternatives on key figures of merit including (minimum detectable target, FOV, etc.) - Quantitatively compare the performance of various space-based sensor architecture and CONOPs alternatives on key figures of merit including (maximizing target detections, catalog maintenance accuracy, space object classification accuracy) - Compile and identify the priority set of signature feature observables based on sensor spectral band, irradiation conditions, and object altitude, size, geometrical/thermal complexity, and dynamic motion - Develop algorithms SSA architectures that address some specialized sensing and identification issues that include space operator/analyst performance response time (based on single or multiple orbital pass observations) and discriminating solar glint from thruster engine burns