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Proceedings Paper

Data association using fused data from multiple sensors
Author(s): Vishnuraj Kittur; Wiley E. Thompson
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Paper Abstract

A data association technique based on the utilization of fused multisensor data which provides a compact description, consisting of both numerical and non - numerical attributes, of the targets present in the surveillance volume. The data association technique is comprised of two processes. The first is the process of seeded clustering --inwhich a cluster is sought around the predicted measurement from the existing track. The data contained in this cluster is fused to obtain a compact description of the targets constituting the cluster. The second is the process of target type matching --in which the target types contained in an existing track are matched with the target types contained in the seeded cluster. The presented method for data association provides a means by which a measure of confidence is assigned to each track (based on the evidence received) and it can be extended in a straight forward manner to handle data association in the context of multi-target tracking.

Paper Details

Date Published: 9 July 1992
PDF: 12 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138256
Show Author Affiliations
Vishnuraj Kittur, New Mexico State Univ. (United States)
Wiley E. Thompson, New Mexico State Univ. (United States)

Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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