In this paper, a new clutter suppression method, named the moving double spectral linear depolarization ratio (MDsLDR) filter, is put forward to mitigate narrow-band clutter in weather radars. The narrow-band clutter observed in the Doppler domain includes: 1) stationary clutter such as ground clutter and 2) nonstationary clutter such as artifacts caused by the radar system itself or external sources. These artifacts are difficult to remove, because they are not confined to specific azimuth and range bins. Based on the difference of the spectral-polarization feature and the spectral continuity of precipitation and clutter, the MDsLDR filter can remove ground clutter, artifacts, and noise. The performance of the newly proposed filter is assessed by data collected by the Doppler-polarimetric IRCTR Drizzle Radar. Three precipitation cases are considered in this paper: moderate/light precipitation, convective precipitation with hook-echo signature, and light precipitation with severe artifact contamination. Furthermore, the implementation of the MDsDLR filter requires relatively low computation complexity, so that the MDsLDR filter can be operated in real time.@en

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. @en

Radar micro-Doppler (m-D) signature, which reflects the micromotion dynamic and structural characteristics of radar target with micromotion, has received increasing attention. Most of the existing m-D signature-extraction methods operate in the time domain or the time-frequency domain. Different from these methods, in this paper, an m-D period estimation approach that operates in the ambiguity domain is proposed. Although the ambiguity function (AF) has been widely used in the field of radar signal processing, its application for m-D signal is introduced for the first time. It is proved that the AF of m-D signal exhibits periodicity along the lag axis and has the best concentration when the lag equals to multiples of the m-D period. Based on this, three AF concentration statistics are employed to capture the periodicity and to provide the m-D estimate. The most important property of the AF concentration statistics is that they are (or approximately) invariant to polynomial translations with terms not larger than second order even if the signal is Doppler ambiguous. Numeric simulation and real radar experiments are used to validate the effectiveness of the proposed technique. @en

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 the 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 variations 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 a weather radar. The first step in implementing this method is the generation of a range-Doppler 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 narrowband moving clutter and noise. Data collected by a polarimetric Doppler weather radar known as the IRCTR Drizzle Radar are used to validate the performance of the proposed algorithm. Moreover, its effectiveness in removing narrowband moving clutter is quantitatively assessed through comparisons with another clutter mitigation method.@en

Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z-R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (KDP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its KDP column (KDP > 3°·km-1) has a liquid water content that is higher than 2.4815 g·m-3, and a high raindrop concentration (Nw) with log10(Nw) exceeding 5.1 mm-1m-3. In addition, small hailstones falling and melting are also found in this event, which further aggregates Nw upon the severe rainfall center in the gap between gauge stations.@en

Weather observation is becoming more important than ever because extreme weather, such as tropical cyclones, thunderstorms and heavy rain, is more common nowadays. To observe and forecast the atmospheric phenomena at high spatial and temporal resolution, weather radar is well recognized as an effective tool. The prerequisite of using weather radar data is sufficient measurement accuracy. The focus of this thesis is to propose advanced techniques in clutter mitigation and calibration for weather radars to improve radar measurement accuracy. On the one hand, clutter mitigation techniques for signal-polarization, dual-polarization without cross-polar measurements and full-polarimetric radar systems are proposed to mitigate different types of clutter. On the other hand, a novel radar calibration technique is developed. With clutter suppression and techniques, clean and correct weather radar measurements are expected to be obtained.@en

Wind turbine clutter has gradually become a concern for the radar community for its increasing size and quantity worldwide. Based on the S-band polarimetric Doppler PARSAX radar measurements, this paper demonstrates the micro-Doppler features and spectral-polarimetric characteristic of wind turbine clutter, the probability distribution functions of different spectral-polarimetric variables. Finally, a simple thresholding method to remove wind turbine clutter is put forward, and its effectiveness can be verified by the measured data. This work is expected to contribute to developing effective algorithms for this dynamic clutter suppression for operational weather radar.@en

For the polarimetric-Doppler weather radar, sometimes there are artifacts caused by radar system itself or external sources displaying in the radar plan position indicator (PPI). These artifacts are not confined to specific range bins and also they are non-stationary when observed in the Doppler domain. This paper puts forward a method to suppress such clutter by designing the generalized spectral linear depolarization ratio (GsLDR) filter. This filter combines the optimal polarization contrast enhancement (OPCE) technique and the double spectral linear depolarization ratio (DsLDR) filter. The success of this filter is mainly based on the polarimetric property difference between precipitation and clutter. The X-band polarimetric-Doppler IRCTR Drizzle Radar (IDRA) data are used to qualitatively and quantitatively verify the performance of the newly proposed filter for radar artifacts suppression.@en