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Innovative Signal Processing Techniques for Mitigation of Wind Turbine Farm Interference in Airborne Radar Systems

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-14-C-0245
Agency Tracking Number: N141-003-0999
Amount: $149,986.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N141-003
Solicitation Number: 2014.1
Timeline
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-05-15
Award End Date (Contract End Date): 2015-07-31
Small Business Information
207 Winchester Dr
New Hartford, NY 13413-1027
United States
DUNS: 000000000
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Vincent Amuso
 Sr. Scientist
 (315) 527-2052
 Upstatescientific@yahoo.com
Business Contact
 alyssa sadallah
Title: Owner/ Operator
Phone: (315) 527-2052
Email: upstatescientific@yahoo.com
Research Institution
 Stub
Abstract

Stationary movers (wind turbines, etc.) adversely affect the interference rejection, detection and tracking processes of airborne radars. This impact is more severe for surveillance of difficult targets (stealth aircraft, slow moving drones, and surface targets). Wind farms are comprised of multiple wind turbines with rotating blades reaching to heights of 500ft. These turbine blades have large RCS and occupy portions of the spatial domain and Doppler spectrum used by E2C and other Navy systems to detect/track critical targets. The UD/UD team proposes to design, evaluate and demonstrate an adjunct Wind Farm Airborne Radar Processor (WARP) for the mitigation of wind farm clutter. The innovation arises in US/UDs proposal for rule based control of training data selection in filtering and false alarm control (in the rejection of clutter). This control will span across multiple channels and Doppler filters. Another proposed innovation is the application of dynamic logic (DL) principles to the hybrid clutter canceller (HCC) described in U.S. Patent #5,061,934 [5]. The HCC will also incorporate a Knowledge Aided Extended (Discrete Time) Kalman Filter KA-EDTKF. The KA-EDTKF will be used for parameter estimation in the WARP for wind turbine backscatter prediction and cancellation with no discernable impact on target visibility.

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

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