On the mitigation of wind turbine clutter for weather radars using range‐Doppler spectral processing

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.

Wind Turbine Clutter Mitigation via Nonconvex Regularizers and Multidimensional Processing

“…WSR-88D Level-I radar data was collected using a Sigmet RVP8 digital receiver at Dodge City, The weather data were collected from an isolated storm at the same range and time instances but located northeast of the radar site. A controlled experimental dataset was created to evaluate the success of the algorithm by using KDDC data by coherently adding the wind turbine signal into the weather signals similar to (Isom et al 2007(Isom et al , 2009Nai et al 2013;Uysal et al 2016). (Details can be found in (Isom et al 2007))…”

“…With the help of spatial and temporal features of wind turbine clutters, researchers (Hood et al 2010) have managed to design an algorithm to detect those clutters automatically. Several techniques, like adaptive spectral processing (Kong et al 2012), signal interpolation (Isom et al 2009), advanced I/Q filtering (Norin 2017) and signal separation (Nguyen and Al-Ashwal 2015;Uysal et al 2014;Nai et al 2013), have been developed to mitigate the dynamic wind turbine clutter for weather radars.…”

Adaptive Beamspace Processing for Phased-Array Weather Radars

“…The delta bias described in [45] and [46] is used to quantify the ability to accurately estimate the radar variables. The delta biases are calculated by subtracting the dish antenna estimates for the volume when no interference is present from the estimates produced by the beamforming methods when interference is present.…”

Practical investigation of multiband mono‐ and bistatic radar signatures of wind turbines

“…In [27] RAM material has been used within the design of a lighting protection system for the turbine, and numerical simulations have been provided to evaluate the RCS reduction effect. Digital signal processing algorithms specifically designed to mitigate the impact of wind farm clutter on radar systems have been also proposed [28][29][30].…”