Multiple Frame Cluster Tracking

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$70,000.00
Award Year:
2002
Program:
SBIR
Phase:
Phase I
Contract:
HQ0006-02-C-0018
Award Id:
58878
Agency Tracking Number:
02-0059
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
PO Box 271246, Ft. Collins, CO, 80527
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
956324362
Principal Investigator:
Aubrey Poore
President
(970) 419-8343
poore@numericainc.com
Business Contact:
Jeff Poore
Vice President
(970) 419-8343
jpoore@numericainc.com
Research Institute:
n/a
Abstract
"The aim of the BMD program is to provide a layered defense against ballistic missile threats.A central component to the BMD system is the tracking system which hasto provide accurate tracks for discrimination and prediction of thethreat's position. Countermeasures in the form of debris, chaff, spentfuel, and balloons can overwhelm any tracking system that tracksonly individual objects. Thus, tracking these groups of objects orclusters followed by transitions to individual object tracking if andwhen individual objects separate from the clusters is a necessarycapability for a robust and real-time tracking system.The objective of the proposed program is to demonstrate feasibility ofmultiple-frame cluster tracking capability for missile defense. Theproposed approach will form multiple clustering hypotheses on each frameof data and base individual frame clustering decisions on theinformation from multiple frames of data in much the same way that MFAor MHT work for individual object tracking. The combination thenpresents a seamless set of algorithms for cluster and individual objecttracking and transitions between the two for BMD. Although appropriateclustering methods are to be investigated, two candidate methods areBayesian EM clustering and the distance based k-means algorithm. Numerica, Inc. has a very successful record of developing algorithms(specifically in the target tracking area), implementing the algorithmsusing highly-struc

* information listed above is at the time of submission.

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