基于卫星遥感资料的近海海上通信环境研究

Research on the Offshore Marine Communication Environment Based on Satellite Remote Sensing Data

海气界面通量等要素会影响海上通信的可靠性和效率。相较于分布零星的海上现场观测数据,卫星遥感数据有覆盖范围广、时间跨度长的优势,基于星载合成孔径雷达风速数据和再分析数据以及浮标实测数据,结合神经网络方法,利用COARE V3.5算法计算海气界面的动量通量、感热通量和潜热通量。研究发现,经过神经网络校正后的SAR风速数据在计算海气通量时,与浮标实测风速的一致性得到了显著提升,摩擦风速的偏差从-0.03 m/s降低到0.01 m/s,风应力的偏差从-0.03 N/m^(2)降低到0.00 N/m^(2),拖曳系数的偏差从-0.29降低到-0.21,潜热通量的偏差从-8.32 W/m^(2)降低到5.41 W/m^(2),感热通量的偏差从0.67 W/m^(2)减小到0.06 W/m^(2)。研究结果表明,经过神经网络校正后的SAR风速资料能够提供更加可靠的海上通信环境数据。

Air-sea interface fluxes significantly impact the reliability and efficiency of maritime communication.Compared to sparse in-situ ocean observations,satellite remote sensing data offers broader coverage and extended temporal span.This study utilizes COARE V3.5 algorithm to calculate momentum flux,sensible heat flux,and latent heat flux at the air-sea interface,based on satellite synthetic aperture radar(SAR)wind speed data,reanalysis data,and buoy measurements,combined with neural network methods.Findings indicate that SAR wind speed data corrected via neural networks show improved consistency with buoy-measured wind speeds in flux calculations.Specifically,the bias in friction velocity decreased from-0.03 m/s to 0.01 m/s,wind stress bias from-0.03 N/m^(2)to 0.00 N/m^(2),drag coefficient bias from-0.29 to-0.21,latent heat flux bias from-8.32 W/m^(2)to 5.41 W/m^(2),and sensible heat flux bias from 0.67 W/m^(2)to 0.06 W/m^(2).Results suggest that the neural network-corrected SAR wind speed data can provide more reliable environmental data for maritime communication.