Jensen–Shannon Distance-Based Filter and Unsupervised Evaluation Metrics for Polarimetric Weather Radar Processing
نویسندگان
چکیده
An effective filtering technique is required for rainfall rate measurement by weather radar. A Jensen–Shannon Distance (JSD) based thresholding filter proposed to mitigate non-meteorological signals, either in clear air or rain situations. This algorithm classifies range-Doppler bins into two classes, hydrometeors and non-hydrometeors, on spectral polarimetric variable features. The result a mask be applied the spectrograms. selected here co-polar correlation coefficient, available dual-polarization full radars. first does global finding an optimized threshold value averaged distribution. Next, classical steps are carried out like ground clutter notch around 0 ms-1, mathematical morphology fill gaps hydrometeor areas removal of narrow Doppler power spectra. second part this article assessment techniques without truth. ground-truth useful select optimal configurations from large solution space. Criteria good defined both time domain. Based those criteria, subjective objective unsupervised evaluation metrics derived, with focus ones. Data including collected X-band radar urban area used. With metrics, JSD-based compared filters. Overall, performs very well considering metrics.
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ژورنال
عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing
سال: 2022
ISSN: ['0196-2892', '1558-0644']
DOI: https://doi.org/10.1109/tgrs.2022.3200731