On the mitigation of wind turbine clutter for weather radars using range‐Doppler spectral processing. Issue 2 (1st February 2013)

• Record Type: Journal Article
• Authors: Nai, Feng; Torres, Sebastián; Palmer, Robert
• Is Part Of: IET radar, sonar & navigation. Volume 7:Issue 2(2013)
• Page Start: 178
• Page End: 190
• Publication Date: 2013-02-01
• Subjects: Doppler radar -- geophysical signal processing -- meteorological radar -- radar clutter -- radar signal processing -- regression analysis -- wind turbines; wind turbine clutter -- weather radars -- range Doppler spectral processing -- automatic algorithms -- return signals -- nonzero Doppler velocity -- range Doppler regression algorithm -- weather signals; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2012.0225
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : The unwanted return signals from wind turbines can contaminate the weather‐radar data that are used by forecasters and automatic algorithms to issue forecast and warnings for severe weather. Since wind turbines have moving components that generate return signals with non‐zero Doppler velocity, traditional ground clutter filters are ineffective at removing wind turbine clutter (WTC). In this study, a WTC mitigation algorithm using the range‐Doppler spectrum is developed and tested with simulated weather and WTC signals. Once the general locations of the WTC contamination are known, the proposed range‐Doppler regression (RDR) algorithm exploits the spatial continuity of weather signals in the range domain to mitigate the WTC contamination while retaining as much weather signal as possible. In contrast to other proposed mitigation algorithms, the RDR algorithm is suited for real‐time implementation on typical operational weather radars. Simulated data are used to optimise the parameters of the algorithm and evaluate its performance for stratiform‐ and convective‐precipitation cases with different degrees of WTC contamination. Finally, a real data case is processed to illustrate the RDR algorithm's effectiveness. The results show that the RDR algorithm has the potential to effectively reduce the bias in spectral‐moment estimates caused by WTC contamination in an operational environment.