Time series analysis model based on electromagnetic detection data
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摘要: 针对电磁探测数据交叉检验时对不同卫星探测数据的时间匹配需求，本文基于DEMETER卫星时序探测数据，分析了国际参考电离层(IRI)模型模拟电子浓度(Ne)数据在不同纬度区域的误差分布特征； 同时，基于自回归移动平均(ARIMA)模型构建了Ne数据时序预测模型. 在此基础上，分析比较IRI模型与ARIMA模型在Ne数据时序预测中的优缺点，结果表明: ARIMA模型模拟预测Ne数据时间序列的相对误差在短期内较低(小于10%)，且随着预测时间的增长而增大； 而IRI模型模拟预测Ne数据时间序列的相对误差不会随着预测时间的增长而增大，且在高纬度地区的预测相对误差比在中低纬度地区低.
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关键词:
- DEMETER卫星 /
- 电子浓度 /
- 国际参考电离层(IRI)模型 /
- 自回归移动平均(ARIMA)模型 /
- 时间序列分析
Abstract: Due to the demand for the time matching of different satellites data during cross-calibration of electromagnetic detection data, this paper analyzes the error distribution features of electron density (Ne) simulated based on the international reference ionosphere (IRI) model at different latitudes by using the time series data of DEMETER satellite. At the same time, based on the autoregre-ssive integrated moving average (ARIMA) model, the Ne data time series forecasting model is constructed. By comparing with the IRI model, the advantages and disadvantages of ARIMA model are analyzed in simulated prediction of the Ne time series data. The results show that the relative error of ARIMA forecasting model is small in the short-time (the relative error less than 10%), however, becomes greater in the long time. Whereas, the relative error of IRI model in simulated prediction of Ne time series data does not become larger in the long time, and the relative error at high latitudes is lower than that at low and moderate latitudes. -
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图 1 (30°E，60°N)处IRI模型预测Ne数据与ISL探测Ne数据的对比
Figure 1. Comparison of Ne data predicted by IRI model to those detected by ISL at (30°E, 60°N)
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图 2 30°E(a)和40°E(b)上不同纬度处IRI模型预测Ne数据与ISL探测Ne数据的平均相对误差分布
Figure 2. Distribution of average relative error of Ne data predicted by IRI model relative to that detected by ISL in different latitude along longitude 30°E (a) and 40°E (b)
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图 3 差分前(a)、后(b) ISL探测的Ne数据月均值时间序列
Figure 3. The time series of monthly average Ne data detected by ISL before (a) and after (b) difference
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图 4 差分后时间序列的自相关图(a)和偏自相关图(b)
Figure 4. Autocorrelation plot (a) and partial autocorrelation plot (b) of time series after difference
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图 5 ARIMA模型预测Ne数据与ISL探测Ne数据的对比
Figure 5. Comparison of Ne data predicted by ARIMA model to those detected by ISL
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图 6 30°E(a)和40°E(b)上不同纬度处ARIMA模型预测Ne数据与ISL探测Ne数据的平均相对误差分布
Figure 6. Distribution of average relative error of Ne data predicted by ARIMA model relative to that detected by ISL in different latitude along longitude 30°E (a) and 40°E (b)
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图 7 2010年1—11月IRI模型和ARIMA模型预测Ne数据与ISL探测Ne数据的相对误差变化图
Figure 7. The variation of relative error of Ne data predicted by IRI model and ARIMA model relative to that detected by ISL in January to November, 2010
表 1 IRI模型和ARIMA模型预测Ne数据与ISL实际探测Ne数据的对比及其相对误差
Table 1 Comparison of Ne data predicted by IRI model and ARIMA model relative to that detected by ISL as well as their relative errors
月份 ISL探测Ne数据 IRI模型 ARIMA模型 预测Ne值 相对误差 预测Ne值 相对误差 1 6.296×109 5.120×109 0.187 5.859×109 0.069 2 6.886×109 7.998×109 0.162 6.869×109 0.002 3 1.203×1010 9.426×109 0.216 1.184×1010 0.016 4 2.056×1010 1.592×1010 0.226 1.883×1010 0.084 5 2.621×1010 2.227×1010 0.150 2.170×1010 0.172 6 2.705×1010 2.371×1010 0.123 2.304×1010 0.148 7 2.515×1010 2.191×1010 0.129 2.038×1010 0.190 8 2.259×1010 1.875×1010 0.170 1.637×1010 0.275 9 1.650×1010 1.422×1010 0.138 1.245×1010 0.245 10 1.014×1010 1.190×1010 0.174 6.461×109 0.363 11 6.072×109 7.243×109 0.193 9.950×109 0.639 
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Liu J, Zhang X M, Wan W X, Shen X H, Ouyang X Y, Shan X J. 2010. Study on the electronic density perturbation detected by DEMETER satellite before Wenchuan earthquake[C]//Proceedings of 2010 IEEE International Geoscience and Remote Sensing Symposium. Honolulu, HI, USA: IEEE: 3382-3385.
Parrot M. 2002. The microsatellite DEMETER: Data registration and data processing[C]//Seismo-Electromagnetics Lithosphere-Atmosphere-Ionosphere Coupling. Tokyo, Japan: TERRAPUB: 391-395.
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