Spectral Polarimetric Features Analysis of Wind Turbine Clutter in Weather Radar

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Chen

et al. 2021

Self Cite

In this paper, a spectral polarimetric filter named moving spectral depolarization ratio (MsDR) filter is proposed to mitigate the effects of clutter and noise for dual-polarization weather radar without cross-polar measurements. The filter is based on a spectral polarimetric variable termed as spectral depolarization ratio (sDR). sDR can be estimated by any polarimetric weather radar, making the MsDR filter widely applicable. Taking advantages of the spectral polarimetric features and the range-Doppler continuity of precipitation, the MsDR filter is implemented in the range-Doppler spectrogram. The performance of the MsDR filter is assessed using data collected by 1) an X-band full-polarimetric radar interfered by narrow-band clutter (both stationary and moving) and sidelobe wind turbine clutter; 2) a C-band operational dual-polarization radar affected by radio frequency interference. In addition, the implementation of the MsDR filter is straightforward, and the computational complexity is relatively low. Hence, the MsDR filter has great potential to be applied in real-time for operational radar systems at different frequencies.Index Terms-Dual-polarization weather radar, clutter mitigation, spectral depolarization ratio, wind turbine clutter, narrowband moving clutter, radio frequency interference.

Section: Introductionmentioning

confidence: 99%

Clutter Mitigation Based on Spectral Depolarization Ratio for Dual-Polarization Weather Radars

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Chen

et al. 2021

Self Cite

“…In addition, combining image processing techniques and the fuzzy logic algorithm, the sea and chaff clutter mitigation technique is proposed in [16]. The weather radar performance is significantly deteriorated by wind turbines because of the large-intensity backscattering from the large tower and rotating blades [17], [18]. Techniques such as interpolation [19], [20], signal decomposition [21], and machine learning [22] are developed to remove the wind turbine clutter.…”

Section: Introductionmentioning

confidence: 99%

Object-Orientated Filter Design in Spectral Domain for Polarimetric Weather Radar

IEEE Trans. Geosci. Remote Sensing

Unal

Russchenberg

2019

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Aiming at removing stationary and moving clutter while retaining precipitation for dual-polarization weather radar, a new clutter suppression method, named the object-orientated spectral polarimetric (OBSpol) filter, is put forward in this paper. Based on the spectral polarimetric feature and the range-Doppler continuity of precipitation, the OBSpol filter generates a filtering mask implemented on the raw range-Doppler spectrogram to mitigate the clutter and noise. The procedures are as follows. After the spectral polarimetric filtering and the mathematical morphology method, one binary mask where "1" indicates the precipitation is obtained. Then, the contiguous bins of the same value "1" in the range-Doppler domain are grouped in areas termed as objects. Whether the produced objects are precipitation or not will be further judged based on appropriate weather radar observable. Thus, combining all the filtered separate objects, a filtering mask can be obtained. In this paper, data collected by the polarimetric Doppler IRCTR drizzle radar are used to demonstrate and assess the performance of the proposed technique in the case of ground clutter, narrowband moving clutter, and noise. Two precipitation cases are examined: 1) moderate precipitation with large scale and 2) light precipitation with severe clutter contamination. In the range-Doppler spectrogram, both stationary and narrowband moving clutters are mitigated, while maintaining nonoverlapping precipitation signal. This helps to solve the problem when clutter and precipitation overlap in the time domain. In addition, the OBSpol filter is proven to be effective with different Doppler velocity resolutions. This technique can be applied in real-time due to its low computation complexity. Moreover, the spectral polarimetric filtering can be designed using the measurements of dual-polarization radar systems which do not have cross-polar measurements. Hence, the proposed clutter mitigation technique can be implemented for operational dual-polarization weather radar.

“…Wind turbine clutter (WTC) is both stationary and non-stationary. It significantly deteriorates radar system performance because of the large-intensity back-scattering from the tower and the moving blades [19]. The undesirable effect of WTC on weather radar is illustrated in [20], [21], on air traffic control radar in [22], and on marine radar in [23].…”

Section: Introductionmentioning

confidence: 99%

Radar Target and Moving Clutter Separation Based on the Low-Rank Matrix Optimization

IEEE Trans. Geosci. Remote Sensing

Unal

Schleiss

et al. 2018

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Abstract-A novel algorithm is put forward to separate radar target and moving clutter based on a combination of the low-rank matrix optimization (LRMO) and a decision tree. Similar to the moving object detection in the field of automated video analysis, the proposed separation method, which is carried out in the range-Doppler domain, makes use of different motion variation of radar target and clutter in the spectrogram sequence. The technique is very general but the focus of this paper is on narrowband moving clutter suppression in weather radar. The first step in implementing this method is the generation of a rangeDoppler spectrogram sequence. Then, the LRMO is applied to the obtained sequence to divide target and moving clutter into foreground and background. From the foreground sequence which is obtained by solving the LRMO, foreground frequency and spectral width are combined in a decision tree to obtain a filtering mask to mitigate the narrow-band moving clutter and noise. Data collected by a polarimetric Doppler weather radar known as the IRCTR Drizzle Radar (IDRA) are used to validate the performance of the proposed algorithm. Moreover, its effectiveness in removing narrow-band moving clutter is quantitatively assessed through comparisons with another clutter mitigation method.