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Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning

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Abstract

Fast ambiguity resolution is a major challenge for GLONASS phase-based applications. The integer-estimable frequency-division multiple-access (IE-FDMA) model succeeds in formulating a set of estimable GLONASS phase ambiguities and preserving the integer property, to which the classical integer ambiguity resolution, typically the least-squares ambiguity decorrelation adjustment (LAMBDA), becomes readily applicable. The initial assessment of the IE-FDMA model demonstrated instantaneous ambiguity resolution capability in case of short-baseline real-time kinematic (RTK) positioning based on ionosphere-fixed formulation, in which the data processing strategy is window (batch)-based least-squares estimation with window length ranging from one to a few epochs. Here, we extend the applicability of the IE-FDMA model to Kalman-filter-based, ionosphere-fixed, ionosphere-weighted, and ionosphere-free cases, which are, respectively, adoptable for short-, medium-, and long-baseline RTK positioning. To adapt the IE-FDMA model to the Kalman filter, we estimate, at each epoch, first the estimable ambiguities, then transform them into integer-estimable ones, and finally resolve them into correct integers. This enables the rigorous integer ambiguity resolution and, at the same time, eases the recursive construction of integer-estimable ambiguities. We analyze global positioning system (GPS) and GLONASS data of nine baselines with lengths varying from several meters to more than one hundred kilometers. The results demonstrate the feasibility of fast ambiguity resolution not only for the GLONASS phase-only short-baseline RTK positioning, but for the GPS + GLONASS medium- and long-baseline RTK positioning as well. In all cases, the fixed solution with faster (several-minutes) convergence and higher (centimeter-level) precision indicates the benefits from GLONASS ambiguity resolution as compared to the float solution. Moreover, the dual-system solution with decreased ambiguity dilution of precision (ADOP) and improved positioning precision confirms the advantages of integrating GLONASS with GPS in contrast to the GPS-only situation.

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Data availability

RINEX data collected in Perth, Australia can be accessed at https://saegnss2.curtin.edu.au/ldc/; RINEX data acquired from the National Geodetic Survey (NGS) CORS network in the United States (US) can be downloaded at ftp://geodesy.noaa.gov/cors/; RINEX data collected in Wuhan, China can be obtained at https://pan.baidu.com/s/1iacpGNmDHgg9JboKiGl_7w (Extraction code: 3r2l).

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Acknowledgments

This work was partially funded by the National Natural Science Foundation of China (No. 41774042), the BDS Industrialization Project (No. GFZX030302030201-2), the Scientific Instrument Developing Project of the Chinese Academy of Sciences (No. YJKYYQ20190063), and the National Key Research Program of China Collaborative Precision Positioning Project (No. 2016YFB0501900). The second author is supported by the CAS Pioneer Hundred Talents Program.

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Authors and Affiliations

  1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China

    Pengyu Hou, Baocheng Zhang & Teng Liu

  2. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China

    Pengyu Hou

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  1. Pengyu Hou
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  2. Baocheng Zhang
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  3. Teng Liu
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Correspondence to Baocheng Zhang.

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Hou, P., Zhang, B. & Liu, T. Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning. GPS Solut 24, 93 (2020). https://doi.org/10.1007/s10291-020-01008-8

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