天文学进展2011，Vol.29Issue(3)：343-352,10.
加权最小二乘法与AR组合模型在极移预测中的应用研究
Joint Model of Weighted Least-squares and AR in Prediction of Polar Motion
摘要
Abstract
Earth rotation parameters (ERPs) include length of day and polar motion. Precise transformations between the international celestial and terrestrial reference frames are needed for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. To perform this transformation, accurate ERPs are necessary. However, the precise measurements of ERPs by space-geodetic techniques have to be pre-processed before the ERPs are available. This causes a delay of 15 to 20 hours in case of GPS and of a few days in case of very-long-baseline interferometry (VLBI) and satellite laser ranging (SLR).Thus it's necessary to predict the ERPs over at least a few days. In addition, it might be interesting to look further into the future to estimate the Earth's rotation in the next few months. Therefore, this paper deals with short-term predictions for next 30 days, long-term predictions for 360 days.Various prediction methods have been developed, such as the joint model of least-squares and AR, joint model of least-squares and artificial neural networks(ANN), and so on. These methods most treat the Chandler Wobble(CW) and Annual Wobble(AW) of the polar motion as constants. However, the CW and AW are of time variant characteristics as a matter of fact. This paper puts forward a new joint model of weighted least-squares(WLS) and AR, according to the time variant characteristics of CW and AW. One important issue in building the WLS+AR model is the right choice of the weight matrix P. According to the statistical properties of the polar motion series, the rule of weight choice is determined: the fitting value nearer to prediction value is given larger weight. In accordance with the rule, three kinds of weight function are built and compared in order to assess the weight function of the weighted least-squares. The more appropriate weight function for X series and Y series are suggested respectively. Finally the WLS+AR model is compared with LS+AR model and shown that the new models are effective for improving the accuracy of the PM prediction. The model is an interesting and new attempt in the PM prediction, and could be seen as an alternative prediction method. However, in the paper, the theoretical basis of the model is not analyzed in depth, and which will be further studied in the later research.关键词
极移预测/加权最小二乘法/AR模型/权函数Key words
Polar Motion Prediction/ Weighted Least-squares/ AR Model/ Weight Function分类
天文与地球科学引用本文复制引用
张昊,王琪洁,朱建军,张晓红..加权最小二乘法与AR组合模型在极移预测中的应用研究[J].天文学进展,2011,29(3):343-352,10.基金项目
国家自然科学基金委员会与中国科学院天文联合基金(10878026) （10878026）
中南大学研究生学位论文创新基金(2011 ssxt054) （2011 ssxt054）
