基于贝叶斯方法的深层充电效应风险模型评估  

Deep charging effect risk model assessment based on Bayesian methods

作　　者：李程 陈东 LI Cheng;CHEN Dong(National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院国家空间科学中心,北京100190 [2]中国科学院大学,北京100049

出　　处：《地球物理学报》2019年第6期1991-2000,共10页Chinese Journal of Geophysics

基　　金：中国科学院创新项目(KGFZD-135-16-013)资助

摘　　要：高能电子穿透航天器并在其内部沉积电荷从而引发深层充电效应,是导致卫星故障的重要因素之一.为了评估深层充电效应诱发卫星异常的风险,本文基于贝叶斯方法,使用一颗地球同步轨道卫星的异常数据和GOES-8卫星的电子通量探测数据,计算了不同能量阈值及累积时间的电子注量、不同卫星配置下模拟仿真的沉积电荷,并分别与卫星异常建立一系列概率风险模型.本文从模型中随机抽样得到模拟异常,并与实测异常构造混淆矩阵以评估模型拟合优度,结果表明>1.0MeV电子3日累积注量-卫星异常概率风险模型为该卫星最优模型.本文利用最优模型对该卫星深层充电效应风险进行了计算,在>1.0MeV电子3日累积注量达到2.0×1010cm-2·sr-1时,该卫星发生深层充电异常的平均后验概率为27%,且95%最小可信值为22%.根据最优模型,我们对该卫星最可能导致异常的部件的材料和结构等特征做出了推断.Deep charging effect is caused by high-energy electrons penetrating spacecraft and depositing charge,which is one of the important factors that inducing satellite failures.In order to quantify the risk of anomalies caused by deep charging,we used the anomalies from a geosynchronous satellite and electron flux measured by GOES-8 satellite to calculate electron fluences with different energy thresholds and cumulative time,and simulated deposited charges with different satellite configurations,a series of probabilistic risk models were established based on Bayesian method by combining the electron fluences and the deposited charges with the satellite anomalies respectively.Using measured anomalies and the simulated anomalies obtained by random sampling from a model,a confusion matrix was constructed to evaluate the goodness-of-fit of a model.The results show that the 3-day >1.0 MeV electron fluence model is the optimal model for this geosynchronous satellite.We calculated the risk of deep charging effect for this satellite,when the 3-day >1.0 MeV electron fluence reaches 2.0×10 10 cm -2 · sr -1,the averaged posterior probability of occurrence of deep charging anomaly for this satellite is 27%,and the 95% least plausible value of that is 22%.The material properties and structures of components which were most likely to result in the anomalies were deduced by the optimal model.

关 键 词：卫星异常 深层充电 贝叶斯方法 风险评估 

分 类 号：P353[天文地球—空间物理学]