| AR模型中AO类异常值探测及其在GPS卫星钟差预报中的应用 |
| |
| 引用本文： | 韩松辉,张国超,张宁,朱建青.AR模型中AO类异常值探测及其在GPS卫星钟差预报中的应用[J].测绘学报,2019,48(10):1225-1235. |
| |
| 作者姓名： | 韩松辉 张国超 张宁 朱建青 |
| |
| 作者单位： | 信息工程大学基础部,河南 郑州,450001;中国人民解放军 78092 部队,四川 成都,610000;苏州科技大学理学院,江苏 苏州,215009 |
| |
| 基金项目： | 国家自然科学基金（41474009；41774038） |
| |
| 摘 要： | 基于EM算法,提出一种AR模型中AO类异常值(additive outlier)探测的算法。该算法可同时进行AR模型拟合与AO类异常值探测,并可有效地解决成片AO类异常值探测时所产生的掩盖和淹没问题。最后,将本文算法应用于GPS卫星钟差预报之中。本文算法可以准确探测出钟差历史观测序列中的AO类异常值,并可对卫星钟差进行精确预报。
|
| 关 键 词： | AR模型 EM算法 AO类异常值 卫星钟差预报 |
| 收稿时间： | 2018-06-12 |
| 修稿时间： | 2019-01-01 |
New algorithm for detecting AO outliers in AR model and its application in the prediction of GPS satellite clock errors |
| |
| HAN Songhui,ZHANG Guochao,ZHANG Ning,ZHU Jianqing.New algorithm for detecting AO outliers in AR model and its application in the prediction of GPS satellite clock errors[J].Acta Geodaetica et Cartographica Sinica,2019,48(10):1225-1235. |
| |
| Authors: | HAN Songhui ZHANG Guochao ZHANG Ning ZHU Jianqing |
| |
| Affiliation: | 1. Department of Basic, Information Engineering University, Zhengzhou 450001, China;2. Troops 78092, Chengdu 610000, China;3. College of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou 215009, China |
| |
| Abstract: | Based on the EM algorithm, an algorithm for detecting additive outlier in an autoregressive (AR) time series is proposed. The algorithm can fit the AR model and detect the additive outlier at the same time, and it can efficiently prevent the occurrence of masking and swamping.At last, the proposed algorithm is applied to process the data of GPS satellite clock error prediction. The examples verify the effectiveness of the algorithm in detecting the additive outlier and predicting the satellite clock error. |
| |
| Keywords: | autoregressive model EM algorithm AO outlier satellite clock error |
| 本文献已被 维普 万方数据 等数据库收录！ |
| 点击此处可从《测绘学报》浏览原始摘要信息 |
|
点击此处可从《测绘学报》下载全文 |
|
