首页> 外文OA文献 >Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments
【2h】

Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments

机译:使用双极化雷达矩对雷达反射率进行模糊逻辑滤波以消除非气象回波

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The ability of a fuzzy logic classifier to dynamically identifynon-meteorological radar echoes is demonstrated using data from the NationalCentre for Atmospheric Science dual polarisation, Doppler, X-band mobileradar. Dynamic filtering of radar echoes is required due to the variablepresence of spurious targets, which can include insects, ground clutter andbackground noise. The fuzzy logic classifier described here uses novelmulti-vertex membership functions which allow a range of distributions to beincorporated into the final decision. These membership functions are derivedusing empirical observations, from a subset of the available radar data. Theclassifier incorporates a threshold of certainty (25 % of the totalpossible membership score) into the final fractional defuzzification toimprove the reliability of the results. It is shown that the addition oflinear texture fields, specifically the texture of the cross-correlationcoefficient, differential phase shift and differential reflectivity, to theclassifier along with standard dual polarisation radar moments enhances theability of the fuzzy classifier to identify multiple features. Examples fromthe Convective Precipitation Experiment (COPE) show the ability of the filterto identify insects (18 August 2013) and ground clutter in the presence ofprecipitation (17 August 2013). Medium-duration rainfall accumulations acrossthe whole of the COPE campaign show the benefit of applying the filter priorto making quantitative precipitation estimates. A second deployment ata second field site (Burn Airfield, 6 October 2014) shows the applicabilityof the method to multiple locations, with small echo features, includingpower lines and cooling towers, being successfully identified by theclassifier without modification of the membership functions from the previousdeployment. The fuzzy logic filter described can also be run in near realtime, with a delay of less than 1 min, allowing its use on future fieldcampaigns.
机译:使用来自美国国家大气科学中心双极化,多普勒,X波段移动雷达的数据,证明了模糊逻辑分类器动态识别非气象雷达回波的能力。由于杂散目标的可变存在,因此需要动态过滤雷达回波,其中可能包括昆虫,地面杂波和背景噪声。这里描述的模糊逻辑分类器使用新颖的多顶点隶属度函数,该函数允许将一定范围的分布合并到最终决策中。这些隶属度函数是使用经验观测值从可用雷达数据的子集中得出的。分类器将确定性阈值(占总可能隶属度分数的25%)合并到最终的分数解模糊中,以提高结果的可靠性。结果表明,将线性纹理场,尤其是互相关系数,差分相移和差分反射率的纹理,与标准双极化雷达矩一起添加到分类器中,可以增强模糊分类器识别多个特征的能力。对流降水实验(COPE)的示例显示了过滤器能够在有降水的情况下(2013年8月18日)识别昆虫(2013年8月18日)和地面杂物(2013年8月17日)。在整个COPE活动中,持续时间中等的降雨积累显示出在进行定量降水估算之前应用过滤器的好处。第二个部署地点和第二个现场站点(Burn Airfield,2014年10月6日)显示了该方法适用于多个位置的情况,分类器已成功识别出具有小的回波特征,包括电力线和冷却塔,而无需修改先前部署的隶属函数。所描述的模糊逻辑滤波器也可以近实时运行,延迟不到1分钟,从而可以在未来的野外活动中使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号