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dc.contributor.authorJones, B.
dc.contributor.authorBryant, D.
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorVo, Ba Tuong
dc.date.accessioned2017-01-30T12:34:12Z
dc.date.available2017-01-30T12:34:12Z
dc.date.created2016-04-26T19:30:23Z
dc.date.issued2015
dc.identifier.citationJones, B. and Bryant, D. and Vo, B. and Vo, B.T. 2015. Challenges of multi-target tracking for space situational awareness, in Proceedings of the 18th International Conference on Information Fusion (Fusion), Jul 6-9 2015, pp. 1278-1285. Washington, DC: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/22881
dc.description.abstract

The tracking of space objects poses unique challenges when compared to traditional applications. Direct application of standard multi-target tracking models fails to yield accurate results for the case of space objects. For example, dynamic models for traditional applications require simple, often linear, discrete-time models. This is not the case for space objects where motion is nonlinear and computation cost is too prohibitive for current Monte Carlo filters. This paper describes the multitarget tracking problem for space objects and summarizes system requirements for space situational awareness. Traditional multitarget filter models are compared to corresponding methods for space object tracking in the context of tracking performance via the d-Generalized Labeled Multi-Bernoulli (d-GLMB) filter. Using these tests, key research challenges for space situational awareness are discussed.

dc.titleChallenges of multi-target tracking for space situational awareness
dc.typeConference Paper
dcterms.source.startPage1278
dcterms.source.endPage1285
dcterms.source.title2015 18th International Conference on Information Fusion, Fusion 2015
dcterms.source.series2015 18th International Conference on Information Fusion, Fusion 2015
dcterms.source.isbn9780982443866
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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