基于电离图运动特性预测的短波频率优选方法  

Frequency Optimization Method Based on Ionogram Motion Characteristics Prediction

作　　者：陈训韬 CHEN Xuntao(Guangzhou Communication Institute,Guangzhou 510310,China)

机构地区：[1]广州通信研究所,广东广州510310

出　　处：《移动通信》2025年第3期117-124,共8页Mobile Communications

摘　　要：针对根据电离图数据进行短波频率优选指配的需求,提出一种基于电离图运动特性预测的短波频率优选方法。首先将短波Chirp探测设备周期性生成的斜向探测电离图序列转换为灰度图像序列。然后基于灰度图的运动特性,进行像素块位置追踪和亮度变化预测,得到灰度图像的未来帧序列。最后基于未来电离图灰度图结合短波监测数据,进行全频段频率排序,在此基础上完成短波频率优选。该方法相比基于MUF参数提取的预测方法,对未来的频率预测信息更加完整,频率优选依据的参数更多,得到的通信频率质量分提升7.5%左右,使得频率优选结果可通概率更高。To address the demand for shortwave frequency optimization based on ionogram data,a shortwave frequency optimization method based on ionogram motion characteristics prediction is proposed.First,the oblique detection ionogram sequences generated periodically by a shortwave Chirp detection device are converted into grayscale image sequences.Then,based on the motion characteristics of the grayscale images,pixel block positioning and brightness variation prediction are performed to obtain the future frame sequences of the grayscale images.Finally,using the future ionogram grayscale images combined with shortwave monitoring data,a frequency sorting across the full frequency band is carried out,followed by shortwave frequency optimization.Compared to the prediction method based on MUF(Maximum Usable Frequency)parameter extraction,this method provides more complete future frequency prediction information,incorporates more parameters for frequency optimization,and improves the communication frequency quality by approximately 7.5%,making the frequency optimization result more reliable.

关 键 词：短波探测 短波通信 电离图 短波频率预测 频率优选算法 

分 类 号：TN929.5[电子电信—通信与信息系统]