基于稳健卡尔曼滤波的倾斜探测电离层MUF短期预报方法  

Short-term prediction method of oblique sounding ionosphere MUF based on robust Kalman filter

作　　者：李国军[1] 郑广发 叶昌荣 周银萍 LI Guojun;ZHENG Guangfa;YE Changrong;ZHOU Yinping(Lab of Beyond LOS Reliable Information Transmission,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学超视距可信信息传输研究所,重庆400065

出　　处：《通信学报》2021年第1期79-86,共8页Journal on Communications

基　　金：国家重点研发计划基金资助项目(No.2019YFC1511300);国家自然科学基金资助项目(No.61671452);重庆市重点研发基金资助项目(No.cstc2017zdcy-zdyfX0011)。

摘　　要：为了改善电离层频率预报准确性低、短波通信连通率差以及工程中观测野值对预报精度影响严重等问题,提出一种基于稳健卡尔曼滤波的倾斜探测电离层MUF短期预报方法。通过研究实测MUF数据的变化规律及观测误差的成因与特征,利用电离层参考模型作为先验信息,改进卡尔曼滤波模型的状态估计方程;引入代价函数机制,通过Huber-M估计实现对预报状态的量测更新,减少观测野值对预报结果的影响,提高所提方法的稳健性。仿真结果表明,所提方法能有效抑制观测野值带来的不利影响,具有较强的稳健性和稳定性。To improve the low accuracy of ionospheric frequency forecasting,poor HF communication connectivity,and the severe impact of observational outliers in engineering on forecast accuracy,a short-term prediction method for oblique detection ionospheric MUF based on robust Kalman filtering was proposed.By studying the variation law of the measured MUF data and the causes as well as characteristics of observation errors,and exploiting the ionospheric reference model as a priori information,the state estimation equation of the Kalman filter model was improved.The cost function mechanism was introduced to realize the measurement update of the forecast state through Huber-M estimation,which reduced the influence of the observation outliers on the forecast results and improves the robustness of the proposed method.The simulation results show that the proposed method can effectively suppress the adverse effects caused by the observation outliers and has good robustness and stability.

关 键 词：短波通信 电离层探测 频率预报 卡尔曼滤波 M估计 

分 类 号：TN92[电子电信—通信与信息系统]