王贵宁, 刘秉义, 冯长中, 吴松华, 刘金涛, 王希涛, 李荣忠. 相干测风激光雷达VAD风场反演的数据质量控制方法[J]. 红外与激光工程, 2018, 47(2): 230002-0230002(8). DOI: 10.3788/IRLA201847.0230002
引用本文: 王贵宁, 刘秉义, 冯长中, 吴松华, 刘金涛, 王希涛, 李荣忠. 相干测风激光雷达VAD风场反演的数据质量控制方法[J]. 红外与激光工程, 2018, 47(2): 230002-0230002(8). DOI: 10.3788/IRLA201847.0230002
Wang Guining, Liu Bingyi, Feng Changzhong, Wu Songhua, Liu Jintao, Wang Xitao, Li Rongzhong. Data quality control method for VAD wind field retrieval based on coherent wind lidar[J]. Infrared and Laser Engineering, 2018, 47(2): 230002-0230002(8). DOI: 10.3788/IRLA201847.0230002
Citation: Wang Guining, Liu Bingyi, Feng Changzhong, Wu Songhua, Liu Jintao, Wang Xitao, Li Rongzhong. Data quality control method for VAD wind field retrieval based on coherent wind lidar[J]. Infrared and Laser Engineering, 2018, 47(2): 230002-0230002(8). DOI: 10.3788/IRLA201847.0230002

相干测风激光雷达VAD风场反演的数据质量控制方法

Data quality control method for VAD wind field retrieval based on coherent wind lidar

  • 摘要: 相干测风激光雷达扫描测量模式下使用速度方位显示(VAD)方法反演水平风场时,若不进行质量控制,会使拟合数据精度大幅降低。基于最小二乘VAD拟合算法,通过分析相干测风激光雷达扫描测量模式中的多种误差源,设置了信噪比、数据残差、扫描区间有效数据、数据有效率四个判据对参与拟合的数据质量进行控制,进而提出了基于以上判据的VAD逐级拟合质量控制方案,设计了数据质量控制流程,并对该方法进行了实验验证。通过对2 955组10 min平均激光雷达测风数据与高精度风杯数据进行对比分析,结果表明:经VAD逐级拟合质量控制流程后,风速均方根偏差从0.97 m/s降低到0.54 m/s,比对偏差降低约44%,风向均方根偏差从7.47降低到5.55,比对偏差降低约26%。

     

    Abstract: The precision of wind filed retrieved from coherent wind lidar scanning measurement mode using VAD method could be substantially low without quality control. By investigating error sources in the scanning measurement mode, based on least square VAD fitting algorithm, a stepwise regression procedure for quality control of the data involved in wind regression was presented. The statistical parameters adopted for the quality control process included SNR, data residual, scanning interval effective data and the data efficiency. Based on the technique proposed, the quality control strategy was designed and verified by comparing the Lidar retrieved 2 955 pair of 10-minuts averaged wind data with those derived from the wind cup data. The result shows that the root mean square deviation (RMSD) of the wind speed has been reduced for approximately 44% from 0.97 m/s to 0.54 m/s, while the RMSD of wind direction has been reduced for approximately 26% from 7.47 to 5.55.

     

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