【本科毕业论文】卫星钟差预报模型的精度分析及评定.doc
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【本科毕业论文】卫星钟差预报模型的精度分析及评定,共49页，字数总计：20633摘要在精密卫星导航定位中，定位的准确性在很大程度上取决于时间测量的准确性，1纳秒的时钟偏差会导致约3米的距离偏差。一个高精度的原子钟可以保证高精度的点位测量的顺利进行。在精密单点定位中，通常采用igs及其数据分析中心提供的钟差数据。然而这些钟差数据往往存在约13天的时间延迟[12]，这给实...
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共49页，字数总计：20633
摘 要
在精密卫星导航定位中，定位的准确性在很大程度上取决于时间测量的准确性，1纳秒的时钟偏差会导致约3米的距离偏差。一个高精度的原子钟可以保证高精度的点位测量的顺利进行。在精密单点定位中，通常采用IGS及其数据分析中心提供的钟差数据。然而这些钟差数据往往存在约13天的时间延迟[12]，这给实时定位带来了不便。另一方面由于IGS提供的广播钟差和预报钟差的精度较低，甚至达不到纳秒级精度，使得单点定位的精度很低。因此，精密钟差数据的实时预报在精密单点定位中非常重要。
本文采用IGS提供的5分钟时间间隔的钟差数据文件，并对其进行建模用以预报未来某个时间步长范围内的钟差数据。为了对模型进行深入的认识和探究，本文采用了四种不同的方法来建模。首先将二次多项式引入钟差预报中，使得模型运算简单，操作便捷，预测精度较高。其次由灰色系统理论知识，对钟差数据归为黑白两类，并建立灰色预报模型，在不同情况下得出了模型的特点。再次通过对应用广泛的卡尔曼模型的认知，建立基于卡尔曼原理的预测模型，并得出了较好的预测精度。然后利用钟差数据和时间序列的关系，通过时间序列原理建立自回归滑动平均（ARMA）模型，对钟差数据进行了简要的分析研究。最后通过比对四种预报模型在不同观测钟差数据长度以及不同预测步长等条件下的预测精度，进行精度分析，总结出各模型特点和最优的应用条件，得出最优预测模型。
关键词：精密单点定位 ; 卫星钟差预报模型 ; 精度分析
Abstract
In the field of precise satellite navigation and positioning, the positioning accuracy depends largely on the accuracy of time measurement. A nanosecond clock deviation will lead to about 3m distance bias .A high-precision atomic clock can ensure high precision point measurement carry out smoothly. The clock error data usually provided by the IGS data analysis centers can be applied in Precise Point Positioning. However, the clock error data often have about 13 days delay, and inconvenience to the real-time location. On the other hand, due to the broadcast clock error and clock error provided by IGS have low prediction accuracy, even the accuracy less than a nanosecond accuracy. It leads a very low accuracy to the point positioning .Therefore, the real-time forecasting of precision clock error data in the precise point positioning is very important.
In this thesis, the interval of 5 minutes IGS clock error data files are modeling for the prediction of the clock difference data in the future time. In order to understand and explore the model deeply, we use four different modeling methods. At first, we introduce the method of quadratic polynomial to the clock error prediction. which makes the model simple and easy operation, what 's more, it makes the model with high prediction accuracy. Secondly, According to the gray system theory, we classified the clock error data into two types in black and white, and establish the gray model. At the same time, we conclude the characteristics of the model in different situations. Thirdly, we used the Kalman model which is applied widely in many kinds of our life. Though the creation of the prediction model based on Kalman principle, we get a better prediction accuracy. Then we used the relationship between the clock data and time series, and establish time-series auto regressive moving average model (ARMA) by the principle of time-series auto regressive moving average. In the meantime, we got a brief analysis of the clock data. Finally, we compared the prediction accuracy of the four prediction model in different conditions of the length of the clock error observational data and prediction step. Then the accuracy of model was analyzed, the model characteristics and optimal application conditions are summarized. The most important thing is to obtain the optimum model.
key words：Precise Point Positioning, Satellite clock error prediction model, Precision analysis
目录
第1章 绪论 1
1.1钟差的提出 1
1.2基础知识简介 1
1.2.1GNSS系统 1
1.2.2卫星导航定位中的误差 2
1.2.3精密单点定位 3
1.2.4精密单点定位的数学模型 4
1.2.5精密单点定位所需解决的问题 4
1.3卫星钟差预报研究现状 5
1.4本文研究的主要内容与方法 5
第2章 卫星钟差预报模型 6
2.1 GPS测量中的钟差文件 6
2.2二次多项式模型 9
2.3卡尔曼预测模型 10
2.4灰色模型 12
2.4.1灰色系统的提出 12
2.4.2灰色系统在钟差预报中的应用 12
2.5自回归滑动平均模型（ARMA） 14
2.5.1ARMA模型的研究历史 14
2.5.2主要函数介绍 14
2.5.3 平稳时间序列的概念 16
2.5.4 平稳时间序列的性质 16
2.5.5 ARMA模型的基本概念 17
2.5.6 ARMA建模的具体步骤 18
2.6模型钟差预测精度评定指标 29
第3章 实例分析 30
3.1数据说明 30
3.2二次多项式模型算例 30
3.3卡尔曼模型算例 31
3.4灰色模型算例 32
3.5 ARMA模型算例 34
3.6不同模型算例对比 36
总结 39
致谢 40
参考文献 41
摘 要
在精密卫星导航定位中，定位的准确性在很大程度上取决于时间测量的准确性，1纳秒的时钟偏差会导致约3米的距离偏差。一个高精度的原子钟可以保证高精度的点位测量的顺利进行。在精密单点定位中，通常采用IGS及其数据分析中心提供的钟差数据。然而这些钟差数据往往存在约13天的时间延迟[12]，这给实时定位带来了不便。另一方面由于IGS提供的广播钟差和预报钟差的精度较低，甚至达不到纳秒级精度，使得单点定位的精度很低。因此，精密钟差数据的实时预报在精密单点定位中非常重要。
本文采用IGS提供的5分钟时间间隔的钟差数据文件，并对其进行建模用以预报未来某个时间步长范围内的钟差数据。为了对模型进行深入的认识和探究，本文采用了四种不同的方法来建模。首先将二次多项式引入钟差预报中，使得模型运算简单，操作便捷，预测精度较高。其次由灰色系统理论知识，对钟差数据归为黑白两类，并建立灰色预报模型，在不同情况下得出了模型的特点。再次通过对应用广泛的卡尔曼模型的认知，建立基于卡尔曼原理的预测模型，并得出了较好的预测精度。然后利用钟差数据和时间序列的关系，通过时间序列原理建立自回归滑动平均（ARMA）模型，对钟差数据进行了简要的分析研究。最后通过比对四种预报模型在不同观测钟差数据长度以及不同预测步长等条件下的预测精度，进行精度分析，总结出各模型特点和最优的应用条件，得出最优预测模型。
关键词：精密单点定位 ; 卫星钟差预报模型 ; 精度分析
Abstract
In the field of precise satellite navigation and positioning, the positioning accuracy depends largely on the accuracy of time measurement. A nanosecond clock deviation will lead to about 3m distance bias .A high-precision atomic clock can ensure high precision point measurement carry out smoothly. The clock error data usually provided by the IGS data analysis centers can be applied in Precise Point Positioning. However, the clock error data often have about 13 days delay, and inconvenience to the real-time location. On the other hand, due to the broadcast clock error and clock error provided by IGS have low prediction accuracy, even the accuracy less than a nanosecond accuracy. It leads a very low accuracy to the point positioning .Therefore, the real-time forecasting of precision clock error data in the precise point positioning is very important.
In this thesis, the interval of 5 minutes IGS clock error data files are modeling for the prediction of the clock difference data in the future time. In order to understand and explore the model deeply, we use four different modeling methods. At first, we introduce the method of quadratic polynomial to the clock error prediction. which makes the model simple and easy operation, what 's more, it makes the model with high prediction accuracy. Secondly, According to the gray system theory, we classified the clock error data into two types in black and white, and establish the gray model. At the same time, we conclude the characteristics of the model in different situations. Thirdly, we used the Kalman model which is applied widely in many kinds of our life. Though the creation of the prediction model based on Kalman principle, we get a better prediction accuracy. Then we used the relationship between the clock data and time series, and establish time-series auto regressive moving average model (ARMA) by the principle of time-series auto regressive moving average. In the meantime, we got a brief analysis of the clock data. Finally, we compared the prediction accuracy of the four prediction model in different conditions of the length of the clock error observational data and prediction step. Then the accuracy of model was analyzed, the model characteristics and optimal application conditions are summarized. The most important thing is to obtain the optimum model.
key words：Precise Point Positioning, Satellite clock error prediction model, Precision analysis
目录
第1章 绪论 1
1.1钟差的提出 1
1.2基础知识简介 1
1.2.1GNSS系统 1
1.2.2卫星导航定位中的误差 2
1.2.3精密单点定位 3
1.2.4精密单点定位的数学模型 4
1.2.5精密单点定位所需解决的问题 4
1.3卫星钟差预报研究现状 5
1.4本文研究的主要内容与方法 5
第2章 卫星钟差预报模型 6
2.1 GPS测量中的钟差文件 6
2.2二次多项式模型 9
2.3卡尔曼预测模型 10
2.4灰色模型 12
2.4.1灰色系统的提出 12
2.4.2灰色系统在钟差预报中的应用 12
2.5自回归滑动平均模型（ARMA） 14
2.5.1ARMA模型的研究历史 14
2.5.2主要函数介绍 14
2.5.3 平稳时间序列的概念 16
2.5.4 平稳时间序列的性质 16
2.5.5 ARMA模型的基本概念 17
2.5.6 ARMA建模的具体步骤 18
2.6模型钟差预测精度评定指标 29
第3章 实例分析 30
3.1数据说明 30
3.2二次多项式模型算例 30
3.3卡尔曼模型算例 31
3.4灰色模型算例 32
3.5 ARMA模型算例 34
3.6不同模型算例对比 36
总结 39
致谢 40
参考文献 41
