WU Wei,ZHOU Yun-jun,LI Xiao-min,et al.Comparative Study on Quality Control Methods of X-band Dual-Polarization Radar Data[J].Journal of Chengdu University of Information Technology,2017,(01):19-27.[doi:10.16836/j.cnki.jcuit.2017.01.004]
X波段双偏振雷达资料的质量控制方法对比研究
- Title:
- Comparative Study on Quality Control Methods of X-band Dual-Polarization Radar Data
- 文章编号:
- 2096-1618(2017)01-0019-09
- 分类号:
- TN959.4
- 文献标志码:
- A
- 摘要:
- 雷达资料的质量控制有各种方法,但比较缺乏不同方法间系统的对比分析。针对中科院大气所X波段双偏振雷达资料进行质量控制,包括了φDP退折叠、滤波、计算KDP、衰减订正等,其中滤波采用滑动平均、中值滤波和小波去噪3种方法对比,衰减订正采用自适应约束算法和ZH-KDP综合算法进行对比,最后进行效果分析。结果表明,质量控制后,有效实现相位退折叠、滤除孤立点和杂波,3种滤波方法对原始数据的毛刺现象都能起到不同程度的抑制,小波去噪的径向距离廓线平滑程度效果最好。两种衰减订正方法后反射率的值有所增加,散点更加密集地分布在拟合曲线附近,其中ZH-KDP综合订正算法订正后的效果相对较好。质控后数据质量改善明显,数据可靠性更高,有助于提高对中小尺度天气的监测、预警和预报的能力。
- Abstract:
- There are various methods to control the quality of radar data, but the comparative analysis among different methods is relatively rare. This paper chooses the X-band dual-polarization radar data to control the quality, including phase unfolding, phase filtering, KDP calculating and attenuation correction, in which phase filtering is compared with the methods of moving average, median filtering and wavelet de-noising and attenuation correction is compared with the self-consistent method and ZH-KDP method. The results indicate that it can work on ground clutter, wrapped phase and statistical fluctuations. The smoothing effect of wavelet filter is the best, while three kinds of filtering methods can suppress the glitch of the original data. The effect of the ZH-KDP method is better, while the value of the reflectivity has increased, scattered points more densely distributed in the vicinity of the fitting curve two attenuation correction methods. The improvement of the quality is obvious after attenuation correction, and the reliability of data show better, which is beneficial to improve the ability of monitoring, early warning and forecasting of meso-and-micro scale weather system.
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备注/Memo
收稿日期:2016-12-15 基金项目:国家重点基础研究发展计划(973 计划)资助项目(2014CB441401); 北京市自然科学基金重点资助项目(8141002); 四川省教育厅资助项目(16CZ0021); 国家科技支撑计划资助项目(2015BAC03B00)