Air-sea water vapor and CO_(2) flux observation experiments were carried out at the Yantai National Satellite Ocean Calibration Platform and the jetty at Monolithic Beach,Juehua Island,using a 100 Hz gas analyzer.The ...Air-sea water vapor and CO_(2) flux observation experiments were carried out at the Yantai National Satellite Ocean Calibration Platform and the jetty at Monolithic Beach,Juehua Island,using a 100 Hz gas analyzer.The observations were corrected by employing wild point rejection,linear detrending,delay correction,coordinate rotation,time matching,and Webb,Pearman,and Leuning(WPL)correction.The results of spectral analysis and a turbulence development adequacy data quality check showed that the overall observation data quality was good.The air-sea water vapor and CO_(2) flux results showed that the observation duration affected both the air-sea flux intensity and direction at different observation frequencies.At shorter observation durations,the air-sea flux values measured at 100 Hz were smaller than the 20 Hz measurements and had opposite directions.In addition,the WPL correction reduced the overall air-sea flux and partially minimized the effect of observation frequency on the air-sea flux intensity.These results showed that high-frequency observations showed more turbulence variations than low-frequency observations.This conclusion could promote an understanding of small-scale turbulence variations.展开更多
随着无线电通信的迅速发展,频谱资源日益紧张,各种干扰问题也越来越严重。其中,900 M Hz频段的干扰问题尤为突出。该文提出了一种基于信号特征分析和机器学习技术的900 MHz频段干扰自动定位方法,通过对干扰信号的频谱、时域、调制等特...随着无线电通信的迅速发展,频谱资源日益紧张,各种干扰问题也越来越严重。其中,900 M Hz频段的干扰问题尤为突出。该文提出了一种基于信号特征分析和机器学习技术的900 MHz频段干扰自动定位方法,通过对干扰信号的频谱、时域、调制等特征进行分析,建立干扰信号特征库,并利用机器学习算法对信号进行分类和定位。实验结果表明,该文提出的方法具有较高的干扰定位准确率和稳定性,能够有效地提高频谱资源利用效率的闭环。展开更多
基金The National Key Research and Development Program of China under contract Nos 2022YFC3104203 and 2018YFC0213103the Science Foundation of Donghai Laboratory under contract No.DH-2022KF01019+1 种基金the National Natural Science Foundation under contract No.419061522023 Shanghai Education Science Research Project under contract No.C2023120.
文摘Air-sea water vapor and CO_(2) flux observation experiments were carried out at the Yantai National Satellite Ocean Calibration Platform and the jetty at Monolithic Beach,Juehua Island,using a 100 Hz gas analyzer.The observations were corrected by employing wild point rejection,linear detrending,delay correction,coordinate rotation,time matching,and Webb,Pearman,and Leuning(WPL)correction.The results of spectral analysis and a turbulence development adequacy data quality check showed that the overall observation data quality was good.The air-sea water vapor and CO_(2) flux results showed that the observation duration affected both the air-sea flux intensity and direction at different observation frequencies.At shorter observation durations,the air-sea flux values measured at 100 Hz were smaller than the 20 Hz measurements and had opposite directions.In addition,the WPL correction reduced the overall air-sea flux and partially minimized the effect of observation frequency on the air-sea flux intensity.These results showed that high-frequency observations showed more turbulence variations than low-frequency observations.This conclusion could promote an understanding of small-scale turbulence variations.
文摘随着无线电通信的迅速发展,频谱资源日益紧张,各种干扰问题也越来越严重。其中,900 M Hz频段的干扰问题尤为突出。该文提出了一种基于信号特征分析和机器学习技术的900 MHz频段干扰自动定位方法,通过对干扰信号的频谱、时域、调制等特征进行分析,建立干扰信号特征库,并利用机器学习算法对信号进行分类和定位。实验结果表明,该文提出的方法具有较高的干扰定位准确率和稳定性,能够有效地提高频谱资源利用效率的闭环。
