臭氧激光雷达硬件故障数据的识别方法  

Identification Method of Ozone Lidar Hardware Failure Data

作　　者：郑朝阳 张天舒 范广强 刘洋 吕立慧 项衍 Zheng Zhaoyang;Zhang Tianshu;Fan Guangqiang;Liu Yang;Lü Lihui;Xiang Yan(Key Laboratory of Environment Optics and Technology,Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Hefei,Anhui 230031,China;University of Science and Technology of China,Hefei,Anhui 230037,China;Institutes of Physical Science and Information Technology,Anhui University,Hefei,Anhui 230039,China)

机构地区：[1]中国科学院安徽光学精密机械研究所环境光学与技术重点实验室,安徽合肥230031 [2]中国科学技术大学,安徽合肥230037 [3]安徽大学物质科学与信息技术研究院,安徽合肥230039

出　　处：《中国激光》2019年第4期151-157,共7页Chinese Journal of Lasers

基　　金：大气重污染成因与治理攻关项目(DDGG0102);国家重点研发计划(2016YFC0200401;2017YFC0213002);国家重点基础研究发展规划项目(2014CB447900);国家自然科学基金项目(41605020)

摘　　要：对大气臭氧探测激光雷达出现硬件故障时的回波特征进行了分析。根据回波形态和雷达强度等,采用基于模糊逻辑的质量控制方法,对雷达硬件故障数据进行了识别检验,识别率高达93%,即能较好地实现对硬件故障数据的质量控制。比较了硬件故障时的数据和被误判的正常数据在300～500 m高度上对应的臭氧浓度和信噪比均值,找出统计特性,降低了对正常数据的误判率。The echo characteristics of the atmospheric ozone detection laser lidar in the event of hardware failure are analyzed.According to the echo shape and intensity of the radar,we use the fuzzy logic-based quality control method to identify and test the lidar hardware failure data.The recognition rate reaches 93%,which means that the method can better realize the quality control of hardware failure data.The mean values of ozone concentration and signal-to-noise ratio(SNR) at the height of 300-500 m of hardware failure data and misjudged normal are compared.The statistical characteristics are found and the false positive rate for data without hardware failure is reduced.

关 键 词：测量 数据质量控制 模糊逻辑 隶属函数 信噪比 臭氧浓度 

分 类 号：P413[天文地球—大气科学及气象学]