Advanced Algorithms for Non-Resolved Space Based Space Sensing

ABSTRACT:The research objective of the proposed effort is to demonstrate and transition an autonomous, rapid determination of satellite features to be used for Threat Indication and Notification (TIN). The scope is to enhance and transition the advanced algorithms previously developed under AFRL/RV into operation in the Joint Space Operations Center (JSPOC) Mission System (JMS) through the JMS Advanced Research Collaboration and Application Development Environment (ARCADE) at AFRL/RV. The goal is for these algorithms to produce higher fidelity monitoring, change detection, and characterization of objects in Deep Space, particularly the geosynchronous (GEO) belt using astrometric and photometric data. Phase II will integrate an enhanced version of the Phase I characterization Resident space object Albedo-area Decomposition (RAD) tool as a web service in ARCADE that provides both satellite features that can used for TIN as well as components of combat ID and a quantified belief that the satellite is operating nominally or anomalously based on the features formed by RADtool.BENEFIT:The first benefit of the proposed approach is the ability to derive satellite features from serendipitous unresolved photometry collected during the metrics mission of the Space Surveillance Network (SSN) sensors, with emphasis on the Space-based Space Surveillance (SBSS) sensor. These routinely collected data sets will be used in lieu of tasked photometry to provide baseline feature values. The second benefit is the ability to monitor satellites with these features to produce a baseline for change detection. The third benefit is higher fidelity change detection using derived satellite features extracted from the photometry. The RAD Web Service is an innovative way to provide higher fidelity change detection on many objects while they remain stable. This complements the current capability that is limited to gross stability assessments (stable versus unstable) performed on only a small subset of objects. The proposed approach is innovative in three ways. First, it requires no new sensors or new Concept of Operations (CONOPS) for existing sensors. Second, it requires no special tasking for Space Object Identification (SOI) tracks, which are a heavy, time-consuming burden for the sensors and thus performable only on a small subset of objects. Third, the algorithms to extract features and detect changes of operational three-axis stabilized satellites are state-of-the-art and near real-time. A diverse set of clients can utilize the SOA implementation of the RAD Web Service in a variety of data fusion applications of interest to commercial and military satellite operators.