Efficient Multitarget Particle Filters for Ground Target Tracking

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,941.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-04-M-1621
Agency Tracking Number:
F041-204-0644
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
NUMERICA CORP.
PO Box 271246, Ft. Collins, CO, 80527
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
956324362
Principal Investigator:
Shawn Herman
Research Scientist II
(970) 419-8343
smherman@numerica.us
Business Contact:
Jeff Poore
Vice President
(970) 419-8343
jbpoore@numerica.us
Research Institution:
n/a
Abstract
Many factors make the ground target tracking problem decidedly nonlinear and non-Gaussian. Some of these factors include the relatively poor angular accuracy of GMTI sensors, the presence of persistent clutter and target obscuration, and the complexity of target maneuvers. Because these difficulties can lead to a multimodal posterior density, a Bayesian filtering solution is more appropriate than a point estimate. In the last decade, the particle filter has emerged as a Bayesian inference technique that is both powerful and simple to implement. The price for this flexibility is almost entirely computational; particle filter run-times can be two orders of magnitude longer than those of Kalman filter variants. In this work, we propose to investigate the design of efficient particle filters for multitarget ground tracking. Using simulated data, we will consider multitarget scenarios involving on-road targets, off-road targets, on-road/off-road transitions, and move-stop-move cycles. Instances of uncertain data association will be produced using closely-spaced targets, stopped targets, clutter, and road intersections. An efficient design will be achieved by adaptively managing the type of particle filters, the number of particles, and the enumeration of hypotheses during data association.

* information listed above is at the time of submission.

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