Measurement-to-track association for nontraditional measurements
dc.contributor.author | Mahler, Ronald | |
dc.date.accessioned | 2017-08-24T02:17:50Z | |
dc.date.available | 2017-08-24T02:17:50Z | |
dc.date.created | 2017-08-23T07:21:50Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Mahler, R. 2011. Measurement-to-track association for nontraditional measurements. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/55247 | |
dc.description.abstract |
Data fusion algorithms must typically address not only kinematic issues - that is, target tracking - but also nonkinematics - for example, target identification, threat estimation, intent assessment, etc. Whereas kinematics involves traditional measurements such as radar detections, nonkinematics typically involves non-traditional measurements such as quantized data, attributes, features, natural-language statements, and inference rules. The kinematic vs. nonkinematic chasm is often bridged by grafting some expert-system approach (fuzzy logic, Dempster-Shafer, rule-based inference) into a single- or multi-hypothesis multitarget tracking algorithm, using ad hoc methods. The purpose of this paper is to show that conventional measurement-to-track association theory can be directly extended to nontraditional measurements in a Bayesian manner. Concepts such as association likelihood, association distance, hypothesis probability, and global nearest-neighbor distance are defined, and explicit formulas are derived for specific kinds of nontraditional evidence. © 2011 IEEE. | |
dc.title | Measurement-to-track association for nontraditional measurements | |
dc.type | Conference Paper | |
dcterms.source.title | Fusion 2011 - 14th International Conference on Information Fusion | |
dcterms.source.series | Fusion 2011 - 14th International Conference on Information Fusion | |
dcterms.source.isbn | 9781457702679 | |
curtin.department | Department of Electrical and Computer Engineering | |
curtin.accessStatus | Fulltext not available |
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