SBIR/STTR Research Award

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

Award identifier 1260eeed81244acf0993e207dbebba0e189ea77cc69669d6615a3c83aeb43989Awarding agency Department of Defense · Missile Defense Agency

Award amount

$70,000

Program and phase

SBIR · Phase I

Award year

2003

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Award details

Awarding agency
Department of Defense
Branch
Missile Defense Agency
Recipient company
ALPHATECH, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
KM4XFJ7CJSY8
Solicitation number
Not reported
Topic code
Not reported

Research 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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

217 SBIR/STTR records share this UEI (1983–2009). Reported award amounts total $62,908,538. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Health and Human Services

Agency intelligence

Department of Defense

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