Large-Scale Simulation of a Process for Cataloguing Small Orbital Debris

Details Large-Scale Simulation of a Process for Cataloguing Small Orbital Debris Large-Scale Simulation of a Process for Cataloguing Small Orbital Debris

Sep 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010amos.confe..28p&link_type=abstract

Proceedings of the Advanced Maui Optical and Space Surveillance Technologies Conference, held in Wailea, Maui, Hawaii, September

Statistics

Computation

Scientific paper

We demonstrate a methodology for establishing orbits for the abundant, un-catalogued, yet dangerous, small orbital debris that will become observable with planned improvements to the Space Fence. Although roughly 15,000 orbital objects are present in the SSN catalog, it is believed that at least 200,000 objects that are massive enough to cause significant damage are in Earth orbit. With improvements to the Space Fence, LEO debris down to 5 cm in size may become observable. The additional hundreds of thousands of observations a day of mostly un-catalogued objects will present a significant data processing challenge. Of particular concern are the large numbers of observations that are uncorrelated either to a known object or to a single object. To deal with the large-scale uncorrelated track (UCT) problem, we have ported the Covariance-Based Track Algorithm (CBTA) into the supercomputer-based Testbed Environment for Space Situational Awareness (TESSA) in order to perform simulations at scale.
CBTA bins UCTs for which initial orbits and initial covariance matrices could be determined back to a common epoch and then uses a statistical measure to see if they correlate given the state vectors and covariance matrices at that common time. If they do, the observations from the two tracks are combined and orbit determination (OD) is used to attempt to fit an orbit to the combined tracks. If OD converges, a new UCT hypothesis is created and the state and covariance of that hypothesis is saved with the other pre-existing UCTs. If a certain number of tracks are successfully combined then they are used to create a new catalog object. Old UCTs are weeded out of the pool of hypotheses when they become obsolete, or when at least some of the observations are used to create a new catalog object.
For the simulation, we developed a Radar detection model simulating the performance of a notional new Space Fence. We propagated thousands of objects over a several day period creating a large number of observations. The methodology that we employed first attempts to match tracks to known orbits using an orbit determination process. Most of the observations cannot be correlated to known orbits and these are routed to the CBTA. We will report on the efficiency with which this hybrid process is able to catalog new objects and on the computational requirements necessary to deal with the problem at scale.

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