An Empirical Tropospheric Delay Model Based on SARIMA

doi:10.13474/j.cnki.11-2246.2018.0068

Abstract

Abstract:

In order to reduce the effect of tropospheric delay and improve the positioning accuracy of GNSS,this paper discusses the possibility of using the prediction model to calculate tropospheric delay in the absence of meteorological parameters,and an empirical tropospheric delay prediction model is proposed:a tropospheric delay prediction method based on the seasonal autoregressive integrated moving average model (SARIMA).Combined with Changchun and Shanghai ZTD data to predict and analyze,the results show that the ZTD forecasting model based on SARIMA can meet the ZTD calculation demand at different time in different regions,and it is a kind of high precision ZTD forecasting method.

Key words: empirical model, tropospheric delay forecast, SARIMA, accuracy improvement

CLC Number:

P228.4

LIU Zhongliu, REN Chao, GAN Xiangqian, LIANG Chunli. An Empirical Tropospheric Delay Model Based on SARIMA[J]. 测绘通报, 2018, 0(3): 14-17,31.

References

[1] 李征航,黄劲松.GPS测量与数据处理[M].武汉:武汉大学出版社,2005.
[2] 赵章明,冯径,洪亮.卫星定位中对流层延迟模型对比分析[J].测绘通报,2016(11):18-21.
[3] 李昭,邱卫宁,邱蕾,等.几种对流层延迟改正模型的分析与比较[J].测绘通报,2009(7):16-18.
[4] 丁晓光.对流层延迟改正在GPS数据处理中的应用与研究[D].西安:长安大学,2009.
[5] 姚宜斌,胡羽丰,余琛.一种改进的全球对流层天顶延迟模型[J].测绘学报,2015,44(3):242-249.
[6] 姚宜斌,张豹,严凤,等.两种精化的对流层延迟改正模型[J].地球物理学报,2015,58(5):1492-1501.
[7] 王勇,张立辉,杨晶.基于BP神经网络的对流层延迟预测研究[J].大地测量与地球动力学,2011,31(3):134-137.
[8] 李剑锋,王永前,郭俊元.预测模型在对流层延迟计算中的应用研究[J].测绘科学技术学报,2015,32(5):450-454.
[9] 吕慧珠,黄文德,闻德保.一种基于频谱分析和AR补偿的对流层延迟预报模型[J].大地测量与地球动力学,2015,35(2):283-286.
[10] 刘军,柴洪洲,刘先冬,等.基于ARIMA(p,1,1)的电离层预报模型[J].大地测量与地球动力学,2010,30(3):79-82.
[11] 刘立龙,陈军,黄良珂,等.基于小波-ARIMA电离层短期总电子含量预报[J].桂林理工大学学报,2016,36(2):294-299.
[12] 张小红,任晓东,吴风波,等.自回归移动平均模型的电离层总电子含量短期预报[J].测绘学报,2014,43(2):118-124.
[13] 朱帮助,林健.基于ARIMA和LSSVM的非线性集成预测模型[J].数学的实践与认识,2009,39(12):34-40.
[14] ZHANG G P.Time Series Forecasting Using a Hybrid ARIMA and Neural Network Model[J].Neurocomputing,2003,50(1):159-175.
[15] 李子奈.计量经济学[M].北京:高等教育出版社,2000.
[16] 张婷.CPI的SARIMA模型与X-12季节调整模型对比预测分析[J].经济问题,2014(12):37-41.