北斗系统GEO/IGSO/MEO卫星观测信息随机特性评估与分析

doi:10.11947/j.AGCS.2020.20190492

测绘学报 ›› 2020, Vol. 49 ›› Issue (12): 1511-1522.doi: 10.11947/j.AGCS.2020.20190492

• 大地测量学与导航 • 下一篇

北斗系统GEO/IGSO/MEO卫星观测信息随机特性评估与分析

高为广¹, 苗维凯², 陈谷仓³, 加松²

1. 北京跟踪与通信技术研究所, 北京 100094;
2. 同济大学测绘与地理信息学院, 上海 200092;
3. 中国卫星导航系统管理办公室, 北京 100034

收稿日期:2019-12-19 修回日期:2020-09-28 发布日期:2020-12-25
通讯作者: 苗维凯 E-mail:wkmiao@tongji.edu.cn
作者简介:高为广(1979-),男,博士,副研究员,研究方向为北斗系统设计与应用。E-mail:gwg9821@163.com
基金资助:
国家自然科学基金（41974041；41874030；42074026）

Evaluation and analysis of stochastic modeling of BeiDou GEO/IGSO/MEO satellite observation

GAO Weiguang¹, MIAO Weikai², CHEN Gucang³, JIA Song²

1. Beijing Institute of Tracking and Telecommunication Technology, Beijing 100094, China;
2. College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China;
3. China Satellite Navigation Office, Beijing 100034, China

Received:2019-12-19 Revised:2020-09-28 Published:2020-12-25
Supported by:
The National Natural Science Foundation of China (Nos. 41974041;41874030;42074026)

摘要/Abstract

摘要： 首先从参数估计、精度评定和质量控制角度论证了在精密定位中随机模型的重要性；然后基于短基线单差观测模型，采用严密的方差分量估计方法计算了不同频率、不同卫星的相位和伪距观测值精度，任意频率之间的交叉相关性以及不同频率的相位和伪距观测值在不同时间间隔上的时间相关性；随后分析了随机模型对基线精度和整体检验统计量的影响。结果表明：北斗用户接收机数据精度都与高度角相关，建议采用高度角指数加权函数；北斗二号3个频率相位观测值之间存在不同程度的相关性，其他类型观测值之间的交叉相关性不明显，不同频率的相位和伪距观测值时间相关性较明显，高精度应用中需关注。另外，正确的随机模型计算的基线精度更接近理论精度。本文为用户正确认识北斗系统3个类型卫星观测信息、正确使用北斗系统提供支撑。

关键词: 随机模型, 交叉相关性, 时间相关性, 北斗系统, 质量控制

Abstract: Firstly, the importance of stochastic model in precise positioning is demonstrated from the perspectives of parameter estimation, accuracy evaluation and quality control. Then, based on the single-difference functional model, the rigorous variance component estimation (VCE) method is used to allow the estimation of satellite-specific variances, cross correlations between two arbitrary frequencies, as well as the time correlations for phase and c+ode observations per frequency. The influence of the stochastic model on baseline precisions and the overall statistics was subsequently analyzed. The results show that the observation precisions of the BeiDou user receiver are overall elevation-dependent for phase and code of all frequencies. It is recommended to use the elevation-dependent exponent weighting model; there are different degrees of correlation between the three frequency phase observations, and the cross correlation between other types of observations is not obvious. The time correlation between phase and code observations of different frequencies is obvious, and attention should be paid to high-precision positioning. Furthermore,the baseline precisions that used the correct stochastic model match the theoretical ones very well for the three baseline components. The paper provides support for users to correctly understand the three types of satellite observation of the BeiDou system and correctly apply the BeiDou system.

Key words: stochastic model, cross correlation, time correlation, BeiDou system, quality control

中图分类号:

P228

高为广, 苗维凯, 陈谷仓, 加松. 北斗系统GEO/IGSO/MEO卫星观测信息随机特性评估与分析[J]. 测绘学报, 2020, 49(12): 1511-1522.

GAO Weiguang, MIAO Weikai, CHEN Gucang, JIA Song. Evaluation and analysis of stochastic modeling of BeiDou GEO/IGSO/MEO satellite observation[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(12): 1511-1522.

参考文献

[1] 杨元喜. 抗差估计理论及其应用[M]. 北京:八一出版社, 1993. YANG Yuanxi. Robust estimation and its applications[M]. Beijing:Bayi Publishing House, 1993.
[2] TEUNISSEN P J G. Testing theory:an introduction[M].2nd ed. Delft:Delft University Press, 2006.
[3] AMIRI-SIMKOOEI A R, ZANGENEH-NEJAD F, ASGARI J. Least-squares variance component estimation applied to GPS geometry-based observation model[J]. Journal of Surveying Engineering, 2013, 139(4):176-187.
[4] TEUNISSEN P J G, AMIRI-SIMKOOEI A R. Least-squares variance component estimation[J]. Journal of Geodesy, 2008, 82(2):65-82.
[5] AMIRI-SIMKOOEI A R, TEUNISSEN P J G, TIBERIUS C C J M. Application of least-squares variance component estimation to GPS observables[J]. Journal of Surveying Engineering, 2009, 135(4):149-160.
[6] TIBERIUS C C J M, KENSELAAR F. Estimation of the stochastic model for GPS code and phase observables[J]. Survey Review, 2000, 35(277):441-454.
[7] EUELER H J, GOAD C C. On optimal filtering of GPS dual frequency observations without using orbit information[J]. Bulletin Géodésique, 1991, 65(2):130-143.
[8] WANG Jinling, STEWART M P, TSAKIRI M. Stochastic modeling for static GPS baseline data processing[J]. Journal of Surveying Engineering, 1998, 124(4):171-181.
[9] LI Bofeng, SHEN Yunzhong, XU Peiliang. Assessment of stochastic models for GPS measurements with different types of receivers[J]. Chinese Science Bulletin, 2008, 53(20):3219-3225.
[10] 李博峰, 沈云中, 楼立志. GPS中长基线观测值随机特性分析[J]. 武汉大学学报(信息科学版), 2010, 35(2):176-180. LI Bofeng, SHEN Yunzhong, LOU Lizhi. Analysis of the stochastic characteristics for medium and long base line GPS measurements[J]. Geomatics and Information Science of Wuhan University, 2010, 35(2):176-180.
[11] 何海波, 杨元喜. GPS观测量先验方差-协方差矩阵实时估计[J]. 测绘学报, 2001, 30(1):42-47. DOI:10.3321/j.issn:1001-1595.2001.01.009. HE Haibo, YANG Yuanxi. Real-time estimation of a prior variance-covariance for GPS observations[J]. Acta Geodaetica et Cartographica Sinica, 2001, 30(1):42-47. DOI:10.3321/j.issn:1001-1595.2001.01.009.
[12] LI Bofeng. Stochastic modeling of triple-frequency BeiDou signals:estimation, assessment and impact analysis[J]. Journal of Geodesy, 2016, 90(7):593-610.
[13] LI Bofeng, ZHANG Lei, VERHAGEN S. Impacts of BeiDou stochastic model on reliability:overall test, w-test and minimal detectable bias[J]. GPS Solutions, 2017, 21(3):1095-1112.
[14] YANG Yuanxi, GAO Weiguang, GUO Shuren, et al. Introduction to BeiDou-3 navigation satellite system[J]. Navigation, 2019, 66(1):7-18.
[15] ZHANG Zhiteng, LI Bofeng, NIE Liangwei, et al. Initial assessment of BeiDou-3 global navigation satellite system:signal quality, RTK and PPP[J]. GPS Solutions, 2019, 23(4):111.
[16] YANG Yuanxi, MAO Yue, SUN Bijiao. Basic performance and future developments of BeiDou global navigation satellite system[J]. Satellite Navigation, 2020, 1(1):1-8.
[17] HELMERT F. Die Ausgleichung nach der Methode der kleinsten quadrate[J]. Auflage, Verlagvon BG Teubner, Leipzig/Berlin, 1907.
[18] 王新洲, 刘经南, 陶本藻. 稳健最优不变二次无偏估计[J]. 武汉测绘科技大学学报, 1995, 20(3):240-245. WANG Xinzhou, LIU Jingnan, TAO Benzao. Robust best invariant quadratic unbiased estimation[J]. Journal of Wuhan Technical University of Surveying and Mapping, 1995, 20(3):240-245.
[19] 於宗俦. Helmert型方差-协方差分量估计的通用公式[J]. 武汉测绘科技大学学报, 1991, 16(2):8-17. YU Zongchou. The general formulas of Helmert type for estimating variance and covarince components[J]. Journal of Wuhan Technical University of Surveying and Mapping, 1991, 16(2):8-17.
[20] RAO C R. Estimation of variance and covariance components-MINQUE theory[J]. Journal of Multivariate Analysis, 1971, 1(3):257-275.
[21] KOCH K R. Parameter estimation and hypothesis testing in linear models[M].Berlin:Springer-Verlag, 1988.
[22] 朱建军. 方差分量的Bayes估计[J]. 测绘学报, 1991, 20(1):1-6. ZHU Jianjun. Bayes estimation of the components of variance[J]. Acta Geodaetica et Cartographica Sinica, 1991, 20(1):1-6.
[23] 李博峰, 沈云中, 楼立志. 基于等效残差的方差-协方差分量估计[J]. 测绘学报, 2010, 39(4):349-354, 363. LI Bofeng,SHEN Yunzhong, LOU Lizhi. Variance-covariance component estimation based on the equivalent residuals[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(4):349-354, 363.
[24] BONA P. Precision, cross correlation, and time correlation of GPS phase and code observations[J]. GPS Solutions, 2000, 4(2):3-13.
[25] XU Peiliang, LIU Jingnan. Variance components in errors-in-variables models:estimability, stability and bias analysis[J]. Journal of Geodesy, 2014, 88(8):719-734.
[26] LI Bofeng, ZHANG Zhetao. Several kinematic data processing methods for time-correlated observations[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(4):1-9.

北斗系统GEO/IGSO/MEO卫星观测信息随机特性评估与分析

Evaluation and analysis of stochastic modeling of BeiDou GEO/IGSO/MEO satellite observation

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	何秀凤, 高壮, 肖儒雅, 罗海滨, 贾东振, 章浙涛. InSAR与北斗/GNSS综合方法监测地表形变研究现状与展望[J]. 测绘学报, 2022, 51(7): 1338-1355.
[2]	王薪普, 薛树强, 曲国庆, 刘以旭, 杨文龙. 水下定位声线扰动分析与分段指数权函数设计[J]. 测绘学报, 2021, 50(7): 982-989.
[3]	朋子涵, 高成发, 刘永胜, 张瑞成, 尚睿. 手机GNSS数据质量提取的变分模态分解法[J]. 测绘学报, 2021, 50(4): 475-486.
[4]	郭树人, 王威, 高为广, 卢鋆, 柴强, 刘文祥, 陈颖. 北斗卫星导航试验验证系统设计与实现[J]. 测绘学报, 2020, 49(9): 1073-1083.
[5]	王猛, 单涛, 王盾. 高轨航天器GNSS技术发展[J]. 测绘学报, 2020, 49(9): 1158-1167.
[6]	王嘉琛, 刘根友, 郭爱智, 肖恭伟, 王彬彬, 高铭, 王生亮. BDS接收机天线相位中心标定[J]. 测绘学报, 2020, 49(3): 312-321.
[7]	赵爽, 王振杰, 刘慧敏. 顾及声线入射角的水下定位随机模型[J]. 测绘学报, 2018, 47(9): 1280-1289.
[8]	杨元喜. 弹性PNT基本框架[J]. 测绘学报, 2018, 47(7): 893-898.
[9]	谭述森. 北斗系统创新发展与前景预测[J]. 测绘学报, 2017, 46(10): 1284-1289.
[10]	黄令勇, 吕志平, 吕浩, 宫轶松. 北斗三频伪距相关随机模型单站建模方法[J]. 测绘学报, 2016, 45(S2): 165-171.
[11]	符京杨, 周建华, 李广云. CNMC方法改进北斗/伪卫星协同定位精度分析[J]. 测绘学报, 2016, 45(S2): 188-193.
[12]	张小红, 朱锋, 薛学铭, 唐龙. 利用Allan方差分析GPS非差随机模型特性[J]. 测绘学报, 2015, 44(2): 119-127.
[13]	潘宗鹏, 柴洪洲, 刘军, 董冰全, 刘鸣, 王华润. 基于部分整周模糊度固定的非差GPS精密单点定位方法[J]. 测绘学报, 2015, 44(11): 1210-1218.
[14]	杨元喜景一帆曾安敏. 自适应参数估计与内外部精度的关系[J]. 测绘学报, 2014, 43(5): 441-445.
[15]	翟国君卞光浪孙君亮李连登项树林童艳. 高空飞行器被动段运行轨迹精密解算方法[J]. 测绘学报, 2014, 43(11): 1109-1117.