Radar-cross-section reduction of wind turbines. part 1.

Brock, Billy C. ; Loui, Hung ; McDonald, Jacob J. ; Paquette, Joshua A. ; Calkins, David A. ; Miller, William K. ; Allen, Steven E. ; Clem, Paul Gilbert ; Patitz, Ward E.

Sandia National Laboratories

关键词: Wind Turbines;    Targets;    Validation;    Air;    Weather;   

DOI  :  10.2172/1038185
RP-ID  :  SAND2012-0480
RP-ID  :  AC04-94AL85000
RP-ID  :  1038185

美国|英语

来源: UNT Digital Library

【 摘 要 】

In recent years, increasing deployment of large wind-turbine farms has become an issue of growing concern for the radar community. The large radar cross section (RCS) presented by wind turbines interferes with radar operation, and the Doppler shift caused by blade rotation causes problems identifying and tracking moving targets. Each new wind-turbine farm installation must be carefully evaluated for potential disruption of radar operation for air defense, air traffic control, weather sensing, and other applications. Several approaches currently exist to minimize conflict between wind-turbine farms and radar installations, including procedural adjustments, radar upgrades, and proper choice of low-impact wind-farm sites, but each has problems with limited effectiveness or prohibitive cost. An alternative approach, heretofore not technically feasible, is to reduce the RCS of wind turbines to the extent that they can be installed near existing radar installations. This report summarizes efforts to reduce wind-turbine RCS, with a particular emphasis on the blades. The report begins with a survey of the wind-turbine RCS-reduction literature to establish a baseline for comparison. The following topics are then addressed: electromagnetic model development and validation, novel material development, integration into wind-turbine fabrication processes, integrated-absorber design, and wind-turbine RCS modeling. Related topics of interest, including alternative mitigation techniques (procedural, at-the-radar, etc.), an introduction to RCS and electromagnetic scattering, and RCS-reduction modeling techniques, can be found in a previous report.