期刊文献+

基于最小二乘和卡尔曼滤波方法进行原子时预报的研究 被引量:10

The Study of Time Prediction Based on the Methods of Least Square and Kalman Filter
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摘要 介绍和分析了最小二乘和卡尔曼滤波方法在时间预报中的应用。通过IGS站提供的钟差数据,分别运用这两种方法对其中六个原子钟进行了时间预报的实验。通过对预报结果进行分析,结论证明为了取得较好的预报效果,不同的预报方法和钟参数的模型对于观测数据的要求有一些差别。从实验数据所成图形来看,当采用一天的观测数据进行模型预报时,最小二乘法的预报精度比卡尔曼滤波法稍高一些。 This paper introduces and analyzes the application of the least square method and Kalman filter in time prediction. Through the clock bias data offered by IGS station, six atomic clocks are under the experiment of time prediction using these two methods. The analysis of prediction results shows that there are differences in the requirements of the observation data for different prediction methods and clock deviation models in order to obtain a better prediction result. According to the figures of the experimental data, we can deduce that the prediction precision of least square method is higher than data in the prediction of the clock deviation model.
出处 《海洋测绘》 2008年第3期24-26,共3页 Hydrographic Surveying and Charting
关键词 最小二乘法 卡尔曼滤波 时间预报 least square method Kalman filter time Kalman filter while adopting one day's observation prediction
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参考文献7

  • 1朱陵凤.时间比对技术研究与原子钟性能分析[D].郑州:信息工程大学测绘学院,2007.
  • 2隋力芬,宋力杰.误差理论与测量平差基础[M].北京:解放军出版社,2004.
  • 3黄维斌.近代平差理论及其应用[M].北京:解放军出版社,1992.
  • 4黄贤源,隋立芬,范澎湃.几种最优滤波方法的分析和比较[J].测绘工程,2007,16(3):35-39. 被引量:12
  • 5杨元喜.动态Kalman滤波模型误差的影响[J].测绘科学,2006,31(1):17-18. 被引量:43
  • 6Thomas E Phipps, Jr. Proper time synchronization [ J ]. Foundations ofPhysics, 1991,21 (9) : 1071-1087.
  • 7Binghao Li, Chris Rizos, Hyung Keun Lee, et al. A GPS- slaved time synchronization system for hybrid navigation[J]. GPS Solut,2006, (10) :207 - 217.

二级参考文献17

  • 1杨元喜.动态系统的抗差Kalman滤波[J].解放军测绘学院学报,1997,14(2):79-84.
  • 2Fagin S L, Recursive Linear Regression Theory, Optimal Filter Theory and Error Analysis of Optimal System [ J ].IEEE Int. Convent, 1964, Record, 12: 216-240.
  • 3Koch K R and Yang Y. Robust Kalman Filter for Rank Deficient Observation Model [ J ]. Journal of Geodesy.1998, 72(8) : 436-441.
  • 4Sage A P and Husa G W. Adaptive filtering with unknown prior statistics [ J ]. Joint American Control Conference,1969 : 769-774.
  • 5Teunissen PJG. An integrity and quality control procedure for use in multi sensor integration [ A ]. In:Proceedings of ION GPS-90 [ C]. Colorado springs, Colorado, USA, 19-21 September, 1990: 513-522.
  • 6Teunissen PJG. Quality control in navigation systems[J ]. IEEE Aerospace and Electronic Systems Magazine, 1990b, 5(7) : 35-41.
  • 7Yang Y, He H and Xu G. Adaptively robust filtering for kinematic geodetic positioning [ J ]. Journal of Geodesy,2001, 75(2/3) : 109-116.
  • 8Yuanxi Yang,Weiguang GAO.An optimal adaptive Kalman filter[J].Journal of Geodesy,2006,80:177-183.
  • 9邓自立.最优滤波理论及其应用-现代时间序列分析方法[M].哈尔滨:哈尔滨工业大学出版社,2003.
  • 10何书元.应用时间序列分析[M].北京:北京大学出版社,2005.

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