短波通信最高可用频率预测算法比较及选择
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摘要
在短波频率管理系统中,实时频率探测技术能够准确获取当前时刻电离层的最高可用频率,但受太阳活动等其他因素的影响,电离层在短时间内可能发生变化,当前时刻实测到的最高可用频率值不足以满足未来一段时间的使用需要。为了解决这一问题,总结了以往项目中使用过的几种基于历史实测数据预测未来一段时间最高可用频率的算法,并对这几种算法的预测效果进行对比分析,最终得出效果最好的修正平均值法,可提升短波选频的时效性。
In the HF frequency management system, the real-time frequency detection technique is able to accurately acquire the maximum usable frequency(MUF) in the ionosphere at the moment. However, the ionosphere would change in a short time due to the factors such as the solar activity that the present MUF would not satisfy the use demand in the future time. In order to deal with it, several algorithms based on historical testing data to predict the MUF in the future time, which were used in the previous projects, were summarized. Their prediction results were compared and analyzed. The revised average value method was derived to enhance the timeliness of HF frequency selection.
In the HF frequency management system, the real-time frequency detection technique is able to accurately acquire the maximum usable frequency(MUF) in the ionosphere at the moment. However, the ionosphere would change in a short time due to the factors such as the solar activity that the present MUF would not satisfy the use demand in the future time. In order to deal with it, several algorithms based on historical testing data to predict the MUF in the future time, which were used in the previous projects, were summarized. Their prediction results were compared and analyzed. The revised average value method was derived to enhance the timeliness of HF frequency selection.
引文
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[2]简相超,郑君里.混沌和神经网络相结合预测短波通信频率参数[J].清华大学学报:自然科学版,2001,41(1):16-19.
[3]Simon Haykin.神经网络原理[M].叶世伟,史忠值,译.北京:机械工业出版社,2006.
[4]彭忠宝,刘昊容.短波天波频率的预测与分析[J].数字通信世界,2016(3):67-69.
[5]沈琪琪,朱德生.短波通信[M].西安:西安电子科技大学出版社,1997.
[6]杨铖,吴永宏,王先义,等.短波通信MUF预测方法的数据分析[J].中国电子科学研究院学报,2014,9(5):512-516.
[7]王骐.短波频率管理系统应用研究[J].中国新通信,2013(10):59-60.
[8]徐彬,吴永宏,刘毅敏.最高可用频率自适应预报算法研究[J].电波科学学报,2011(4):699-703.