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Suppression of Wind Turbine Clutter from Radar Data

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-13-C-0035
Agency Tracking Number: F12B-T05-0114
Amount: $149,919.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF12-BT05
Solicitation Number: 2012.B
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-04-16
Award End Date (Contract End Date): 2014-01-16
Small Business Information
1300 Research Park Dr
Dayton, OH -
United States
DUNS: 363384004
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Matt Ferrara
 Staff Engineer
 (937) 427-8433
Business Contact
 Carri Miller
Title: Contracts Manager
Phone: (937) 427-8433
Research Institution
 Colorado State University
 Anaya, Lisa
2002 Campus Delivery
Fort Collins, CO 80523-0523
United States

 (970) 491-0537
 Nonprofit College or University

ABSTRACT: It is well known that wind turbine clutter (WTC) presents a significant challenge to detecting targets in civilian and military applications. The large radar cross section (RCS) of wind turbines, combined with their significant range of Doppler spread, make traditional clutter mitigation techniques effectively useless. The objective of this Phase I effort is to develop a physically consistent mathematical model which will accurately characterize the backscattered radar response of wind turbines in a low-order manner amenable to the Phase II signal processing algorithm design. Ultimately, the Phase II objective is to utilize the model developed in Phase I to remove the WTC signature from the data without affecting the delicate response of much lower RCS moving targets such as aircraft. Matrix Research will develop a model that sufficiently characterizes the physics of the clutter yet is simple enough to allow for practical implementation within real-time airborne-target detection algorithm. BENEFIT: The model developed in this effort, along with its associated clutter-mitigation algorithm, will provide a revolutionary new capability for improving detection performance of both existing and future radar assets. This capability is an enabler for a wide range of radar technologies in various business sectors such as defense (e.g., early warning radar), air traffic control, and weather prediction.

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

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