基于模糊逻辑法的粒子识别研究

浏览次数： 13

分享到:

摘要:

毫米波雷达相比于微波雷达对云的探测具有更高的敏感性,本文利用Chilbolton观测场的94GHz毫米波云雷达的基本探测量,结合探空仪的温度廓线数据,根据Shupe总结得到的云粒子相态识别的阈值,采用模糊逻辑算法对一次实际探测进行了反演研究.该模糊逻辑算法采用的主要隶属函数为不对称的梯形函数,识别粒子的相态类别主要分成雨、毛毛雨、液态水、混合相态、冰、雪等6种,对比经典的阈值算法反演的过冷水区域结果后认为,本文所研究的模糊逻辑算法对云中水凝物粒子的相态识别分类基本合理,其反演的结果对于人工影响天气作业以及飞机安全飞行等方面具有重要的意义.

COmpared to the microwave radar, the millimeter-wave radar is more sensitive in detecting cloud. In this pa- per, combined with the radiosonde temperature profile data, the basic quantity of 94GHz millimeter-wave cloud radar in Chilbo- Iron probe observation field is utilized. According to the threshold of cloud particle phase state recognition summarized by Shupe, a fuzzy logic algorithm is employed for inversion of a practical detection. The membership function of fuzzy logic algo- rithm is the asymmetric trapezoidal function, and the phase states of particle identification are mainly divided into rain, drizzle, liquid water, mixed phase, ice and snow. In comparison to the classical threshold algorithm for inversion of super-cooled water area, the results show that the proposed fuzzy logic algorithm for phase states classification of cloud hydrometeors particle is rational. The inversion results are significant for marx-made weather modification project, the safety of aircraft flight and so on.

作者:

范盼王金虎陈军

机构地区:

南京信息工程大学江苏省气象探测与信息处理重点实验室南京信息工程大学中国气象局气溶胶云降水重点开放实验室

出处:

《betway官方app 学报：自然科学版》 CAS 北大核心 2016年第3期47-52,共6页

基金:

国家科技部公益性(气象)行业专项(GYHY201206038) 国家自然科学基金(61372066) 江苏省普通高校研究生科研创新计划(CXLX12-0500)

关键词:

毫米波雷达探空温度模糊逻辑粒子相态识别过冷水识别

millimeter-wavelength cloud radar radiosonde temperature fuzzy logic particle phase identification cold wa- ter identification

分类号: