Scalable Conjunction Processing using Spatiotemporally Indexed Ephemeris Data
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Senior Research Scientist
Senior Research Scientist
AbstractABSTRACT: Stellar Science has developed innovative techniques for satellite conjunction processing using spatiotemporally indexed ephemeris data. Our algorithms first insert each satellite into a spatially aware data structure, such as a K-D Tree or a Spatial Hash Table, and then it scans the data structure looking for satellite conjunctions. While traditional approaches to satellite conjunction analysis have polynomial runtimes (O(n^2)), this spatial indexing approach are capable of achieving linearithmic (On*log(n)) or even linear (O(n)) runtimes, depending on which data structure is used and how efficiently it is tuned. In phase I, Stellar Science has demonstrated the feasibility of these concepts and created prototype filtering plug-ins for the CAOS-D Conjunction Analysis architecture. In phase II, we will build upon and expand this initial proof of concept through several comprehensive test and refine algorithm development cycles. The algorithms will be validated using current space object catalogs and also future proofed using catalogs containing up to 100,000 space objects. We will also develop an analyst tool that will help characterize the performance characteristics of various filtering algorithms and chains of filtering algorithms. BENEFIT: Timely and accurate conjunction filtering is a critical need of the Joint Space Operations Center (JSpOC). The collision warnings produced by the JSpOC are of critical importance in protecting U.S. and allied spacecraft against destructive collisions, and in protecting the lives of astronauts during space flight. By reducing the number of objects requiring high-fidelity and computationally-intensive conjunction analysis, Stellar Science will enable the JSpOC to continue to perform its mission in the future as the number of tracked space objects and debris particles grows to exceed 100,000. In addition to benefitting JSpOC, this technology can be used to aid the Naval Space Command (NSC), the National Aeronautics and Space Administration (NASA), the European Space Agency (ESA), and commercial satellite owners and operators in protecting their valuable and irreplaceable space assets from space debris. Future commercialization applications also include air traffic control, a domain that also requires predicting and avoiding collisions among multiple fast-moving objects.
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