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Tracking Performance Self-Determination and Prediction for Sensor Data Fusion…

Award Information

Agency:
Department of Defense 		Branch:
Air Force 		Award ID:
82203 		Program Year/Program:
2007 / SBIR
Agency Tracking Number:
F071-232-2632 		Solicitation Year:
N/A 		Solicitation Topic Code:
N/A 		Solicitation Number:
N/A
Small Business Information
Sigtem Technology, Inc.
1343 Parrott Drive San Mateo, CA -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2007
Title: Tracking Performance Self-Determination and Prediction for Sensor Data Fusion and Resource Management
Agency / Branch: DOD / USAF
Contract: FA8650-07-M-1162
Award Amount: $99,990.00
 

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.

Principal Investigator:

Chun Yang
Principal Scientist
2155656868
chunyang@sigtem.com

Business Contact:

Chun Yang
President
2155656868
chunyang@sigtem.com
Small Business Information at Submission:

SIGTEM TECHNOLOGY, INC.
P.O. Box 5546 San Mateo, CA 94402

EIN/Tax ID: 233012783
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No