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Physical Model-Based Target Discrimination in Clutter using Surface-Based Radar

Award Information

Agency:
Department of Defense
Branch:
Missile Defense Agency
Award ID:
64156
Program Year/Program:
2003 / SBIR
Agency Tracking Number:
031-0301
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
ALPHATECH, INC.
6 New England Executive Park Burlington, MA 01803
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2003
Title: Physical Model-Based Target Discrimination in Clutter using Surface-Based Radar
Agency / Branch: DOD / MDA
Contract: F3361503M4129
Award Amount: $70,000.00
 

Abstract:

With the appropriate processing algorithms, surface-based radar has the potential to discriminate reentry vehicles from other threat objects in the presence of clutter, which is a critical part of the BMD problem. Discrimination is based on resolving theobjects in range, and characterizing each object's shape and motion. The algorithm we propose is the model-based approach, which applies a hypothesize-and-test loop to compare radar data with a physical model of the data. In this approach, featuresextracted from the collected radar data are matched with features predicted from a series of scene hypotheses. The predictions use a physical model of the scene objects, including motion and shape, and run this through a signature prediction code. Thehypothesis search proceeds until an optimal shape and motion match for each object is found. Our other applications indicate that the model-based approach will offer several distinct advantages over rule-based and template methods, such as robustperformance in clutter. In this SBIR, we propose to develop algorithms to extract radar features and compare them with match metrics that perform well in the presence of countermeasures. We will then evaluate the discrimination performance of themodel-based approach with simulated clutter scenarios in Phase I. The technology developed under this program will contribute directly to the MDA objective of improving threat object classification from radar data for a variety of targets and under avariety of conditions. Specifically, the model-based approach will improve discrimination and kinematic parameter estimation of threat objects in the presence of countermeasures such as chaff. Furthermore, we anticipate that the development of themodel-based methods in this SBIR will provide advanced capabilities for commercial and law enforcement applications in high noise environments such as communications, surveillance, industrial and medical image processing, and civilian radar systems.

Principal Investigator:

William C. Snyder
Lead Research Engineer
7812733388
wsnyder@alphatech.com

Business Contact:

John J. Barry
Contracts Manager
7812733388
jbarry@alphatech.com
Small Business Information at Submission:

ALPHATECH, INC.
6 New England Executive Park Burlington, MA 01803

EIN/Tax ID: 042654515
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No