Determining inter-system bias of GNSS signals with narrowly spaced frequencies for GNSS positioning

Relative positioning using multi-GNSS (global navigation satellite systems) can improve accuracy, reliability, and availability compared to the use of a single constellation system. Intra-system double-difference (DD) ambiguities (ISDDAs) refer to the DD ambiguities between satellites of a single constellation system and can be fixed to an integer to derive the precise fixed solution. Inter-system ambiguities, which denote the DD ambiguities between different constellation systems, can also be fixed to integers on overlapping frequencies, once the inter-system bias (ISB) is removed. Compared with fixing ISDDAs, fixing both integer intra- and inter-system DD ambiguities (IIDDAs) means an increase of positioning precision through an integration of multiple GNSS constellations. Previously, researchers have studied IIDDA fixing with systems of the same frequencies, but not with systems of different frequencies. Integer IIDDAs can be determined from single-difference (SD) ambiguities, even if the frequencies of multi-GNSS signals used in the positioning are different. In this study, we investigated IIDDA fixing for multi-GNSS signals of narrowly spaced frequencies. First, the inter-system DD models of multi-GNSS signals of different frequencies are introduced, and the strategy for compensating for ISB is presented. The ISB is decomposed into three parts: 1) a float approximate ISB number that can be considered equal to the ISB of code pseudorange observations and thus can be estimated through single point positioning (SPP); 2) a number that is a multiple of the GNSS signal wavelength; and 3) a fractional ISB part, with a magnitude smaller than a single wavelength. Then, the relationship between intra- and inter-system DD ambiguity RATIO values and ISB was investigated by integrating GPS L1 and GLONASS L1 signals. In our numerical analyses with short baselines, the ISB parameter and IIDDA were successfully fixed, even if the number of observed satellites in each system was small.

[1]  Robert Odolinski,et al.  Combined BDS, Galileo, QZSS and GPS single-frequency RTK , 2014, GPS Solutions.

[2]  Dmitry Kozlov,et al.  CENTIMETER-LEVEL, REAL TIME KINEMATIC POSITIONING WITH GPS + GLONASS C/A RECEIVERS , 1998 .

[3]  Dennis Odijk,et al.  ESTIMATION OF DIFFERENTIAL INTER-SYSTEM BIASES BETWEEN THE OVERLAPPING FREQUENCIES OF GPS , GALILEO , BEIDOU AND QZSS , 2013 .

[4]  H.-J. Euler,et al.  On a Measure for the Discernibility between Different Ambiguity Solutions in the Static-Kinematic GPS-Mode , 1991 .

[5]  Pawel Wielgosz,et al.  Accounting for Galileo–GPS inter-system biases in precise satellite positioning , 2014, Journal of Geodesy.

[6]  Simon Banville,et al.  GLONASS ionosphere-free ambiguity resolution for precise point positioning , 2016, Journal of Geodesy.

[7]  Alfred Leick,et al.  GLONASS Satellite Surveying , 1998 .

[8]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[9]  Dennis Odijk,et al.  Galileo IOV RTK positioning: standalone and combined with GPS , 2014 .

[10]  Maorong Ge,et al.  Particle filter-based estimation of inter-frequency phase bias for real-time GLONASS integer ambiguity resolution , 2015, Journal of Geodesy.

[11]  Peter Teunissen,et al.  Characterization of between-receiver GPS-Galileo inter-system biases and their effect on mixed ambiguity resolution , 2013, GPS Solutions.

[12]  Yang Gao,et al.  Modeling and assessment of combined GPS/GLONASS precise point positioning , 2013, GPS Solutions.

[13]  Peter Teunissen,et al.  GPS Observation Equations and Positioning Concepts , 1998 .

[14]  Chris Rizos,et al.  A Comparative Study of Mathematical Modelling for GPS/GLONASS Real-Time Kinematic (RTK) , 2012 .

[15]  Tao Li,et al.  Comparing the mathematical models for GPS&GLONASS integration , 2011 .

[16]  Dmitry Kozlov,et al.  Statistical Characterization of Hardware Biases in GPS+GLONASS Receivers , 2000 .

[17]  Michael Meindl Combined Analysis of Observations from Different Global Navigation Satellite Systems , 2011 .

[18]  O. Montenbruck,et al.  IGS-MGEX: Preparing the Ground for Multi-Constellation GNSS Science , 2013 .

[19]  Chris Rizos,et al.  GPS and GLONASS Integration: Modeling and Ambiguity Resolution Issues , 2001, GPS Solutions.

[20]  K. Jong,et al.  Interchangeable Integration of GPS and GLONASS by Using a Common System Clock in PPP , 2013 .

[21]  Xingxing Li,et al.  Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo , 2015, Journal of Geodesy.

[22]  P. Teunissen,et al.  The ratio test for future GNSS ambiguity resolution , 2013, GPS Solutions.

[23]  Christian Rocken,et al.  Obtaining single path phase delays from GPS double differences , 2000 .

[24]  Niklas Hallberg,et al.  Modeling and Assessment of Systems Security , 2008, MODSEC@MoDELS.

[25]  D. A. Force,et al.  Combined Global Navigation Satellite Systems in the Space Service Volume , 2015 .

[26]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[27]  Lambert Wanninger,et al.  Carrier-phase inter-frequency biases of GLONASS receivers , 2012, Journal of Geodesy.

[28]  Peter Teunissen,et al.  Assessing the IRNSS L5-signal in combination with GPS, Galileo, and QZSS L5/E5a-signals for positioning and navigation , 2016, GPS Solutions.

[29]  Shaowei Han,et al.  Quality-control issues relating to instantaneous ambiguity resolution for real-time GPS kinematic positioning , 1996 .

[30]  Maorong Ge,et al.  Particle filter-based estimation of inter-system phase bias for real-time integer ambiguity resolution , 2017, GPS Solutions.