基于稳健卡尔曼滤波的倾斜探测电离层MUF短期预报方法

doi:10.11959/j.issn.1000-436x.2021011

Abstract

Abstract:

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.

Key words: HF communication, ionosphere detection, frequency prediction, Kalman filter, M-estimation

CLC Number:

TN92

Guojun LI, Guangfa ZHENG, Changrong YE, Yinping ZHOU. Short-term prediction method of oblique sounding ionosphere MUF based on robust Kalman filter[J]. Journal on Communications, 2021, 42(1): 79-86.

Figures/Tables 9

References 23

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站点	RKF		KF		IRI		备注
站点	均方根误差/MHz	相对误差	均方根误差/MHz	相对误差	均方根误差/MHz	相对误差	备注
重庆—海南	0.551 3	5.65%	0.573 1	5.55%	1.759 7	12.09%	无野值
海南—重庆	0.691 9	6.22%	0.703 1	6.04%	1.718 2	12.83%	无野值
重庆—昆明	0.517 8	7.36%	0.466 2	6.96%	0.849 3	9.44%	无野值
昆明—重庆	0.606 4	8.61%	1.373 4	12.20%	1.074 7	14.57%	有野值

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

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