Show simple item record

dc.contributor.authorMahler, Ronald
dc.identifier.citationMahler, R. 2011. Measurement-to-track association for nontraditional measurements.

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.titleMeasurement-to-track association for nontraditional measurements
dc.typeConference Paper
dcterms.source.titleFusion 2011 - 14th International Conference on Information Fusion
dcterms.source.seriesFusion 2011 - 14th International Conference on Information Fusion
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record