北斗三频观测值强电离层条件下的周跳探测与修复

发布时间：2018-02-16 20:06

本文关键词： 磁暴无几何相位电离层延迟神经网络周跳　出处：《中国惯性技术学报》2017年01期 　论文类型：期刊论文

【摘要】：采用伪距相位组合和无几何相位组合作为周跳探测量,分析了无几何相位组合的漏探率和误探率,并给出了该组合的适用条件。针对强电离层条件下误探率较高的缺点,提出了采用RBF(Radial basis function)神经网络模型对一阶电离层延迟变化量进行预测,并根据预测残差判断周跳是否发生,采用电离层延迟改正的相位组合周跳估值进行周跳修复。利用电离层活跃期间的北斗三频观测数据验证所提出的算法,实验结果表明:该模型即使在大磁暴发生期间也能够准确地探测出所有周跳并正确修复,不存在不敏感周跳组合,同时误探率在0.3%以下。
[Abstract]:Using pseudo-range phase combination and non-geometric phase combination as cycle slip detectives, the leakage rate and false detection rate of geometric phase combination are analyzed, and the applicable conditions of this combination are given. In view of the disadvantages of high error detection rate under strong ionospheric conditions, the pseudo-range phase combination and non-geometric phase combination are used to analyze the leakage rate and false detection rate of the combination. In this paper, RBF(Radial basis function neural network model is used to predict the first order ionospheric delay variation, and the cycle slip is judged according to the predicted residual error. The phase combination cycle slip estimation of ionospheric delay correction is used to repair the cycle slip. The proposed algorithm is verified by using the Beidou three-frequency observation data during the active period of the ionosphere. The experimental results show that the model can accurately detect all cycle slips and correct repair even during the occurrence of large magnetic storms, and there is no insensitive cycle slip combination, and the false detection rate is below 0.3%.
【作者单位】：中国矿业大学国土环境与灾害监测国家测绘地理信息局重点实验室;
【基金】：国家重点研发计划资助项目(2016YFC0803103)
【分类号】：P228

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