手机GNSS数据质量提取的变分模态分解法

doi:10.11947/j.AGCS.2021.20200258

测绘学报 ›› 2021, Vol. 50 ›› Issue (4): 475-486.doi: 10.11947/j.AGCS.2021.20200258

手机GNSS数据质量提取的变分模态分解法

朋子涵, 高成发, 刘永胜, 张瑞成, 尚睿

东南大学交通学院, 江苏南京 211189

收稿日期:2020-06-24 修回日期:2021-02-05 发布日期:2021-04-28
通讯作者: 高成发 E-mail:gaochfa@163.com
作者简介:朋子涵(1996—),男,博士生,研究方向为手机GNSS精密定位。E-mail:pzhseu@163.com
基金资助:
国家自然科学基金（41974030）；智能手机室内外一体化融合定位算法技术支撑服务（8521008666）

Variational mode decomposition method for estimation of GNSS data quality from a smartphone

PENG Zihan, GAO Chengfa, LIU Yongsheng, ZHANG Ruicheng, SHANG Rui

School of Transportation, Southeast University, Nanjing 211189, China

Received:2020-06-24 Revised:2021-02-05 Published:2021-04-28
Supported by:
The National Natural Science Foundation of China (No. 41974030);The Indoor and Outdoor Integrated Fusion Positioning Algorithm Technical Support Service for Smartphone (No. 8521008666)

摘要/Abstract

摘要： 观测噪声提取是数据质量分析与随机模型构建的基础。当前手机GNSS观测噪声提取主要采用三阶差分法与历元间差分法，这些方法的提取结果都会受到卫星相关性和历元间相关性的影响。本文提出结合变分模态分解（variational mode decomposition，VMD）提取手机观测噪声的方法。模拟分解试验表明：VMD能够较好地对混合信号进行分解。提取小米8手机GNSS观测噪声并进行分析，结果表明：GPS、BDS和Galileo 3系统伪距观测噪声计算结果一致，GLONASS系统伪距噪声大约是其他系统的两倍，四系统的载波观测噪声相当，手机GNSS观测噪声与Android系统版本无关。相比于高度角随机模型，载噪比随机模型更适用于手机GNSS定位。利用数据质量提取结果拟合载噪比随机模型，并进行定位试验。定位结果表明：相对于高度角随机模型，采用载噪比随机模型后手机伪距单点定位效果能提升25%以上。手机PPP平面定位结果能收敛至0.6 m以内，高程定位精度收敛至1.2 m以内。

关键词: 手机GNSS, 变分模态分解, 质量分析, 随机模型

Abstract: At present, the third-derivative approach or the inter-epoch difference method is mainly used to calculate the GNSS observation noise of the smartphone, but the results of these approaches will be affected by satellite correlation and time correlation. Aimed to the GNSS data noise estimation of smartphones, we propose an approach of noise estimation method based onvariational mode decomposition (VMD). Firstly, it uses VMD to extract low-frequency components of double-difference observations, then inversely calculates the single-difference observations of each satellite, and finally calculates the observation noise of each satellite. Simulation decomposition experiments show that VMD can decompose mixed signals satisfactorily. The analysis results of the GNSS data quality from the Xiaomi 8 indicate that the pseudorange noise of GPS, BDS and Galileo are analogous. The pseudorange noise of GLONASS is about twice that of the other systems, and the phase noise of the four systems are coincident. Observation noise will not be influenced by the operating system. In addition, the carrier-to-noise ratio stochastic model is more suitable for GNSS positioning of smartphones than elevation stochastic model. Compared with the using of latter model, the single point positioning effect of smartphones can be improved by more than 25% after using the carrier-to-noise ratio model. The PPP results of the smartphone can converge to within 0.6 and 1.2 m in horizontal and vertical components, respectively.

Key words: smartphone GNSS, variational mode decomposition, quality analysis, stochastic model

中图分类号:

P228

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.

PENG Zihan, GAO Chengfa, LIU Yongsheng, ZHANG Ruicheng, SHANG Rui. Variational mode decomposition method for estimation of GNSS data quality from a smartphone[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(4): 475-486.

参考文献

[1] YANG Yuanxi. Resilient PNT concept frame[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(3):1-7. DOI:10.11947/j.JGGS.2019.0301.
[2] JIANG Chen, ZHANG Shubi, CAO Yizhi, et al. A robust fault detection algorithm for the GNSS/INS integrated navigation systems[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(1):12-24. DOI:10.11947/j.JGGS.2020.0102.
[3] PESYNA K M, HUMPHREYS T E, HEATH R W, et al. Exploiting antenna motion for faster initialization of centimeter-accurate GNSS positioning with low-cost antennas[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(4):1597-1613.
[4] PESYNA JR K M, HEATH JR R W, HUMPHREYS T E. Centimeter positioning with a smartphone-quality GNSS antenna[C]//Proceedings of the 27th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+2014). Tampa, FL:The Institute of Navigation, 2014:1568-1577.
[5] HUMPHREYS T E, MURRIAN M, VAN DIGGELEN F, et al. On the feasibility of cm-accurate positioning via a smartphone's antenna and GNSS chip[C]//Proceedings of 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS). Savannah, GA:IEEE, 2016:232-242.
[6] BANVILLE S, VAN DIGGELEN F. Precise GNSS for everyone:precise positioning using raw GPS measurements from android smartphones[J]. GPS World, 2016, 27(11):43-48.
[7] PIRAZZI G, MAZZONI A, BIAGI L, et al. Preliminary performance analysis with a GPS+Galileo enabled chipset embedded in a smartphone[C]//Proceedings of 2017 ION GNSS+. Portland, Oregon:The Institute of Navigation, 2017:101-115.
[8] REALINI E, CALDERA S, PERTUSINI L, et al. Precise GNSS positioning using smart devices[J]. Sensors, 2017, 17(10):2434.
[9] DABOVE P, PIETRA V D. Single-baseline RTK positioning using dual-frequency GNSS receivers inside smartphones[J]. Sensors, 2019, 19(19):4302.
[10] DABOVE P, PIETRA V D. Towards high accuracy GNSS real-time positioning with smartphones[J]. Advances in Space Research, 2019, 63(1):94-102.
[11] CHEN Bo, GAO Chengfa, LIU Yongsheng, et al. Real-time precise point positioning with a Xiaomi MI 8 android smartphone[J]. Sensors, 2019, 19(12):2835.
[12] LACHAPELLE G, GRATTON P. GNSS precise point positioning with android smartphones and comparison with high performance receivers[C]//Proceedings of 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). Chongqing, China:IEEE, 2019:1-13.
[13] NETTHONGLANG C, THONGTAN T, SATIRAPOD C. GNSS precise positioning determinations using smartphones[C]//Proceedings of 2019 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS). Bangkok, Thailand:IEEE, 2019:401-404.
[14] ZHANG Xiaohong, TAO Xianlu, ZHU Feng, et al. Quality assessment of GNSS observations from an Android N smartphone and positioning performance analysis using time-differenced filtering approach[J]. GPS Solutions, 2018, 22(3):70.
[15] HÅKANSSON M. Characterization of GNSS observations from a Nexus 9 Android tablet[J]. GPS Solutions, 2019, 23(1):21.
[16] GENG Jianghui, JIANG Enming, LI Guangcai, et al. An improved hatch filter algorithm towards sub-meter positioning using only android raw GNSS measurements without external augmentation corrections[J]. Remote Sensing, 2019, 11(14):1679.
[17] ZHANG Kaishi, JIAO Wenhai, WANG Liang, et al. Smart-RTK:multi-GNSS kinematic positioning approach on android smart devices with doppler-smoothed-code filter and constant acceleration model[J]. Advances in Space Research, 2019, 64(9):1662-1674.
[18] 陈波, 高成发, 刘永胜, 等. 安卓手机终端原始GNSS观测数据质量分析[J]. 导航定位学报, 2019, 7(3):87-95. CHEN Bo, GAO Chengfa, LIU Yongsheng, et al. Quality analysis on raw GNSS measurements of Android mobile terminals[J]. Journal of Navigation and Positioning, 2019, 7(3):87-95.
[19] LIU Yongsheng, GAO Chengfa, CHEN Bo, et al. Pseudo-range single point and differential positioning accuracy test based on android smartphone[M]//SUN Jiadong, YANG Changfeng, YANG Yuanxi, et al. China Satellite Navigation Conference. Singapore:Springer, 2019:72-81.
[20] LIU Wanke, SHI Xiang, ZHU Feng, et al. Quality analysis of multi-GNSS raw observations and a velocity-aided positioning approach based on smartphones[J]. Advances in Space Research, 2019, 63(8):2358-2377.
[21] PESYNA JR K M, HEATH JR R W, HUMPHREYS T E. Accuracy in the palm of your hand centimeter positioning with a smartphone-quality GNSS antenna[J]. GPS World, 2015, 26(2):16-30.
[22] LI Guangcai, GENG Jianghui. Characteristics of raw multi-GNSS measurement error from Google Android smart devices[J]. GPS Solutions, 2019, 23(3):90.
[23] GOGOI N, MINETTO A, LINTY N, et al. A controlled-environment quality assessment of android GNSS raw measurements[J]. Electronics, 2019, 8(1):5.
[24] PAZIEWSKI J, SIERADZKI R, B. Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones[J]. GPS Solutions, 2019, 23(4):98.
[25] ZHANG Ruicheng, GAO Chengfa, PAN Shuguo, et al. Fusion of GNSS and speedometer based on VMD and its application in bridge deformation monitoring[J]. Sensors, 2020, 20(3):694.
[26] DRAGOMIRETSKIY K, ZOSSO D. Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3):531-544.
[27] 李博峰, 沈云中, 徐培亮. 不同GPS接收机观测值的随机模型评估[J]. 科学通报, 2008, 53(16):1967-1972. LI Bofeng, SHEN Yunzhong, XU Peiliang. Stochastic model evaluation of different GPS receiver observations[J]. Chinese Science Bulletin, 2008, 53(16):1967-1972.

手机GNSS数据质量提取的变分模态分解法

Variational mode decomposition method for estimation of GNSS data quality from a smartphone

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

编辑推荐

Metrics

本文评价

[1]	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.
[2]	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.
[3]	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.
[4]	杨元喜. 弹性PNT基本框架[J]. 测绘学报, 2018, 47(7): 893-898.
[5]	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.
[6]	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.
[7]	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.
[8]	周泽波,沈云中,李博峰. GPS/Doppler导航随机模型的移动窗口实时估计算法[J]. 测绘学报, 2011, 40(2): 220-225.