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Radar Centroid Processing Algorithm with Tracker Feedback

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-05-C-0362
Agency Tracking Number: N052-118-0494
Amount: $149,999.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N05-118
Solicitation Number: 2005.2
Timeline
Solicitation Year: 2005
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-08-29
Award End Date (Contract End Date): 2006-03-01
Small Business Information
40 Lloyd Avenue, Suite 200
Malvern, PA 19355
United States
DUNS: 075485425
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 C. Butler
 Vice President
 (757) 727-7700
 Allen.Butler@va.wagner.com
Business Contact
 W. Reynolds Monach
Title: Vice President
Phone: (757) 727-7700
Email: reynolds@va.wagner.com
Research Institution
N/A
Abstract

The raw detection data provided by a radar typically consists of primitive measurements that correspond to discrete range-bearing cells. A single target can generate multiple primitive detections in adjacent range-bearing cells as the radar beam scans across it; the radar system therefore employs a centroid processing algorithm to combine the primitive measurements and form a single merged detection report to pass along to the tracker. However, if multiple targets exist close to one another, this clustering process can produce undesirable results such as track degradation and/or track drop, since the measurements for more than one target may be combined to produce a single report. Here, we propose a method for utilizing feedback from the tracker to produce the appropriate number of centroid estimates in a given area, thus avoiding track drop. Our method is a modification of the Expectation-Maximization algorithm as applied to the Gaussian Mixture Estimation problem; accordingly, we will refer to our algorithm as EMARCT (an Expectation Maximization Algorithm for Radar Centroid processing with Tracker feedback). In Phase I we will develop the algorithm in greater detail, program it in a high-level language such as matlab, and demonstrate its feasibility on simulated data.

* Information listed above is at the time of submission. *

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