Modeling of LEO orbital debris populations for ORDEM2008 |
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Authors: | Y.-L. Xu M. Horstman P.H. Krisko J.-C. Liou M. Matney E.G. Stansbery C.L. Stokely D. Whitlock |
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Affiliation: | 1. ESCG, Mail Code JE104, 2224 Bay Area Blvd., Houston, TX 77058, USA;2. Orbital Debris Program Office, NASA Johnson Space Center, NASA, 2101 NASA Parkway, Houston, TX 77058, USA |
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Abstract: | The NASA Orbital Debris Engineering Model, ORDEM2000, is in the process of being updated to a new version: ORDEM2008. The data-driven ORDEM covers a spectrum of object size from 10 μm to greater than 1 m, and ranging from LEO (low Earth orbit) to GEO (geosynchronous orbit) altitude regimes. ORDEM2008 centimeter-sized populations are statistically derived from Haystack and HAX (the Haystack Auxiliary) radar data, while micron-sized populations are estimated from shuttle impact records. Each of the model populations consists of a large number of orbits with specified orbital elements, the number of objects on each orbit (with corresponding uncertainty), and the size, type, and material assignment for each object. This paper describes the general methodology and procedure commonly used in the statistical inference of the ORDEM2008 LEO debris populations. Major steps in the population derivations include data analysis, reference-population construction, definition of model parameters in terms of reference populations, linking model parameters with data, seeking best estimates for the model parameters, uncertainty analysis, and assessment of the outcomes. To demonstrate the population-derivation process and to validate the Bayesian statistical model applied in the population derivations throughout, this paper uses illustrative examples for the special cases of large-size (>1 m, >32 cm, and >10 cm) populations that are tracked by SSN (the Space Surveillance Network) and also monitored by Haystack and HAX radars operating in a staring mode. |
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Keywords: | Orbital debris Environment Modeling Radar data analysis Inverse problem with positive constrains Bayesian technique |
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