Analysis and modelling of pseudorange and carrier-phase biases in GNSS Precise Point Positioning

被引:0
|
作者
Aggrey, John [1 ]
Bisnath, Sunil [1 ]
机构
[1] York Univ, Dept Earth & Space Sci & Engn, Toronto, ON M3J 2R7, Canada
来源
PROCEEDINGS OF THE 27TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2014) | 2014年
关键词
GLONASS; RESOLUTION; GPS;
D O I
暂无
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Unlike GPS, GLONASS observations are affected by the Frequency Division Multiple Access (FDMA) satellite signal structure, which introduces inter-frequency channel biases (ICBs) and other system biases. The effects of these biases are visible in the pseudorange and carrier-phase residuals, which affect GNSS Precise Point Positioning (PPP) convergence period, un-differenced ambiguity resolution and overall positioning accuracy. Current research has shown the correlation between receiver stations from heterogeneous networks, such as the International GNSS Service (IGS), in PPP processing and the increase in magnitude of the pseudorange and carrier-phase ICBs in GLONASS-only PPP solutions. Discounting other system biases which may be present, the correlation is due to mixed receiver and antenna hardware types, differences in firmware versions, and irregularities in the updates of the receiver equipment at the stations. With new and expanding satellite constellations, it is expected that PPP convergence period will decrease due to improved geometry, more observations and stronger signals. However, the inclusion of GLONASS has introduced additional biases that need to be accounted for in the data processing or else this relationship will not hold. So, does the current performance of GLONASS PPP reflect the limits of the processing technique or by accurate modelling of GLONASS biases, can there be improvements in the solution accuracy and reliability? And can the behaviour of the ICBs help mitigate the effect of these biases that compromise the solution integrity of GLONASS PPP? With an increasing number of receiver and antenna hardware types available, the error modelling for the pseudorange and carrier-phase biases becomes more complex. In the GNSS community, there is only a limited understanding of these equipment biases, which introduce varying magnitudes of observable error due to each receiver-antenna combination. A strong correlation between the pseudorange and carrier-phase inter-channel biases and receiver firmware and antennas exists, which relates to the differences that exist in the estimated inter-channel biases and similar firmware of the same receiver types. Currently, there is no standard correction format for PPP users in relation to these biases given a specific receiver firmware or antenna type. This research proposes a possible GLONASS inter-frequency channel bias correction using 350 IGS stations, based on 32 receiver types and 8 antenna types, by observing the unique trends observed in the bias estimates in relation to the GLONASS satellites. Given the unique trends of the inter-channel frequency biases with respect to frequency channels, receiver and antenna types, modelling the pseudorange ICBs show an improvement in the initial convergence period of 20 minutes with a reduction of 13% for GLONASS PPP. While these pseudorange and carrier-phase equipment biases do not cause significant long-term errors on GLONASS PPP positioning results, and have almost no effect on GPS PPP results, they impact initial float ambiguity and associated float covariance estimates. By improving these estimates, more accurate fixed PPP solutions can be produced and more quickly. Further analysis will be done to evaluate the realism of the associated float covariances with bias modelling, and the impact on PPP fixed solutions.
引用
收藏
页码:2512 / 2522
页数:11
相关论文
共 50 条
  • [31] Multipath extraction and mitigation for high-rate multi-GNSS precise point positioning
    Zheng, Kai
    Zhang, Xiaohong
    Li, Pan
    Li, Xingxing
    Ge, Maorong
    Guo, Fei
    Sang, Jizhang
    Schuh, Harald
    JOURNAL OF GEODESY, 2019, 93 (10) : 2037 - 2051
  • [32] An Assessment of the Precise Products on Static Precise Point Positioning using Multi-Constellation GNSS
    Mohammed, Jareer
    Moore, Terry
    Hill, Chris
    Bingley, Richard M.
    2018 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM (PLANS), 2018, : 634 - 641
  • [33] A review on the inter-frequency biases of GLONASS carrier-phase data
    Geng, Jianghui
    Zhao, Qile
    Shi, Chuang
    Liu, Jingnan
    JOURNAL OF GEODESY, 2017, 91 (03) : 329 - 340
  • [34] ASSESSMENT OF MULTI-GNSS PRECISE ORBIT AND CLOCK PRODUCTS FROM DIFFERENT ANALYSIS CENTERS BASED ON PRECISE POINT POSITIONING
    Li, Weiguo
    Kacmarik, Michal
    ACTA GEODYNAMICA ET GEOMATERIALIA, 2021, 18 (03): : 387 - 397
  • [35] Orbital Artifacts in Multi-GNSS Precise Point Positioning Time Series
    Zajdel, Radoslaw
    Kazmierski, Kamil
    Sosnica, Krzysztof
    JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 2022, 127 (02)
  • [36] Impact of elevation mask on multi-GNSS precise point positioning performance
    Wu, Yi bin
    Liu, Yanyan
    Yi, Wenting
    Ge, Hong bin
    EARTH SCIENCE INFORMATICS, 2021, 14 (03) : 1111 - 1120
  • [37] Multi-GNSS precise point positioning (MGPPP) using raw observations
    Liu, Teng
    Yuan, Yunbin
    Zhang, Baocheng
    Wang, Ningbo
    Tan, Bingfeng
    Chen, Yongchang
    JOURNAL OF GEODESY, 2017, 91 (03) : 253 - 268
  • [38] Impact Analysis of Differential Code Biases of GPS Satellites on the Kinematic Precise Point Positioning
    Zhang, Shoujian
    Zhao, Lei
    CHINA SATELLITE NAVIGATION CONFERENCE (CSNC) 2015 PROCEEDINGS, VOL I, 2015, 340 : 283 - 289
  • [39] Multi-GNSS precise point positioning for precision agriculture
    Guo, Jing
    Li, Xingxing
    Li, Zhenhong
    Hu, Leyin
    Yang, Guijun
    Zhao, Chunjiang
    Fairbairn, David
    Watson, David
    Ge, Maorong
    PRECISION AGRICULTURE, 2018, 19 (05) : 895 - 911
  • [40] Multi-GNSS Single Frequency Precise Point Positioning
    Innac, Anna
    Gaglione, Salvatore
    Angrisano, Antonio
    2018 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR THE SEA; LEARNING TO MEASURE SEA HEALTH PARAMETERS (METROSEA), 2018, : 222 - 226