Tracking Performance Self-Determination and Prediction for Sensor Data Fusion and Resource Management

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,990.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-07-M-1162
Award Id:
82203
Agency Tracking Number:
F071-232-2632
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
P.O. Box 5546, San Mateo, CA, 94402
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
869012732
Principal Investigator:
Chun Yang
Principal Scientist
(215) 565-6868
chunyang@sigtem.com
Business Contact:
Chun Yang
President
(215) 565-6868
chunyang@sigtem.com
Research Institution:
n/a
Abstract
We propose to develop a tracking performance self-determination methodology with which a tracker can assess its operational conditions and predict its performance. With the self-determined performance metrics, a sensor resource manager can efficiently reroute or reschedule the radar activities so as to resolve data association ambiguity and ensure the overall track quality. In Phase I, a model for a tracker integrated with a sensor resource manager will be established for closed-loop simulation. Self-determined performance metrics will be introduced in comparison to absolute performance metrics which require the truth trajectory not available in run time. In addition to analytic derivation for simple cases, complex performance curves will be obtained in designed experiments via computer simulation. Key influence factors will be assessed including target maneuver and data association. A deferred updating with an interval smoother is proposed to solve data association ambiguity of crossing targets. In Phase II, the Phase I-validated methods will be extended with a comprehensive set of metrics, information needs, and theoretical performance capabilities over various operating conditions.

* information listed above is at the time of submission.

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