Suppression of Wind Turbine Clutter from Radar Data

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$149,919.00
Award Year:
2013
Program:
STTR
Phase:
Phase I
Contract:
FA9550-13-C-0035
Award Id:
n/a
Agency Tracking Number:
F12B-T05-0114
Solicitation Year:
2012
Solicitation Topic Code:
AF12-BT05
Solicitation Number:
2012.B
Small Business Information
1300 Research Park Dr, Dayton, OH, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
363384004
Principal Investigator:
Matt Ferrara
Staff Engineer
(937) 427-8433
matt.ferrara@matrixresearch.com
Business Contact:
Carri Miller
Contracts Manager
(937) 427-8433
carri.miller@matrixresearch.com
Research Institute:
Colorado State University
Anaya, Lisa
2002 Campus Delivery
Fort Collins, CO, 80523-0523
(970) 491-0537
Nonprofit college or university
Abstract
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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