General Science and Philosophy

    

Association Performance Enhancement Through Classification

Authors: Quirin Hamp, Leonhard Reindl

Association of spatial information about targets is conventionally based on measures such as the Euclidean or the Mahalanobis distance. These approaches produce satisfactory results when targets are more distant than the resolution of the employed sensing principle, but is limited if they lie closer. This paper describes an association method combined with classification enhancing performance. The method not only considers spatial distance, but also information about class membership during a post-processing step.Association of measurements that cannot be uniquely associated to only one estimate, but to multiple estimates, is achieved under the constraint of conflict minimization of the combination of mutual class memberships.

Comments: 9 Pages.

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Submission history

[v1] 2014-12-04 00:35:56

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