Innovative Filtering Techniques for Ground Target Tracking

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$749,949.00
Award Year:
2005
Program:
SBIR
Phase:
Phase II
Contract:
FA8650-05-C-1807
Award Id:
67733
Agency Tracking Number:
F041-204-1650
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
40 Lloyd Avenue, Suite 200, Malvern, PA, 19355
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
075485425
Principal Investigator:
BarryBelkin
President
(610) 644-3400
bbelkin@pa.wagner.com
Business Contact:
JohnEldridge
Treasurer
(610) 644-3400
GovtMktg@pa.wagner.com
Research Institute:
n/a
Abstract
The project focus is the development of a ground target tracking algorithm to support the JSTARS radar operating in the GMTI mode. Multiple hypothesis tracking (MHT) algorithms maintain alternative data associations to represent report-to-track association ambiguities. In Phase 1 we developed a prototype MHT algorithm not requiring the Bayes' posterior distribution for the target state to be Gaussian. State estimation is accomplished using the deformation method, a form of particle filtering (sequential Monte Carlo state estimation) that requires neither hypothesis pruning nor hypothesis regeneration. The deformation method transforms existing target state estimates into samples that closely approximate draws from the Bayes' posterior distribution for the target state. Data association is treated as an assignment problem and is solved using the Munkres algorithm. The smooth deformation of the continuous target state variables is through the action of a stochastic differential equation. The discontinuous deformation of the discrete target state variables is through the application of the Metropolis algorithm. In Phase 2 we will incorporate the processing of target signature information from high range resolution (HRR) data. We also will model the effects of terrain on vehicle motion and observability. Certain computations will be parallelized to reduce the algorithm execution time.

* information listed above is at the time of submission.

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