Acta Geodaetica et Cartographica Sinica ›› 2019, Vol. 48 ›› Issue (10): 1225-1235.doi: 10.11947/j.AGCS.2019.20180271

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New algorithm for detecting AO outliers in AR model and its application in the prediction of GPS satellite clock errors

HAN Songhui1, ZHANG Guochao2, ZHANG Ning1, ZHU Jianqing3   

  1. 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
  • Received:2018-06-12 Revised:2019-01-01 Online:2019-10-20 Published:2019-10-24
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41474009;41774038)

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.

Key words: autoregressive model, EM algorithm, AO outlier, satellite clock error

CLC Number: