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Measures of effectiveness for BMD mid-course tracking on MIMD massively parallel computers
Author(s) -
John P. VanDyke,
James L. Tomkins,
M.D. Furnish
Publication year - 1995
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/83111
Subject(s) - computer science , mimd , massively parallel , code (set theory) , course (navigation) , tracking (education) , parallel computing , track (disk drive) , function (biology) , object (grammar) , set (abstract data type) , measure (data warehouse) , artificial intelligence , operating system , programming language , psychology , pedagogy , physics , astronomy , evolutionary biology , database , biology
The TRC code, a mid-course tracking code for ballistic missiles, has previously been implemented on a 1024-processor MIMD (Multiple Instruction -- Multiple Data) massively parallel computer. Measures of Effectiveness (MOE) for this algorithm have been developed for this computing environment. The MOE code is run in parallel with the TRC code. Particularly useful MOEs include the number of missed objects (real objects for which the TRC algorithm did not construct a track); of ghost tracks (tracks not corresponding to a real object); of redundant tracks (multiple tracks corresponding to a single real object); and of unresolved objects (multiple objects corresponding to a single track). All of these are expressed as a function of time, and tend to maximize during the time in which real objects are spawned (multiple reentry vehicles per post-boost vehicle). As well, it is possible to measure the track-truth separation as a function of time. A set of calculations is presented illustrating these MOEs as a function of time for a case with 99 post-boost vehicles, each of which spawns 9 reentry vehicles

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