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Maximum Ratio Principle-Based Estimation of Difference Inter-System Bias

Published online by Cambridge University Press:  13 August 2020

Zihan Peng ,
Chengfa Gao  and
Rui Shang
Zihan Peng
Affiliation:
(School of Transportation, Southeast University, Nanjing, Jiangsu, China)
Chengfa Gao*
Affiliation:
(School of Transportation, Southeast University, Nanjing, Jiangsu, China)
Rui Shang
Affiliation:
(School of Transportation, Southeast University, Nanjing, Jiangsu, China)
*
(E-mail: gaochfa_seu@163.com)
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Abstract

The tight combination model improves the positioning accuracy of the Global Navigation Satellite System (GNSS) in complex environments by increasing the redundancy of observation. However, the ambiguity cannot be calculated directly because of the correlation between it and the phase difference inter-system bias (DISB) in the model. This paper proposes a method of DISB estimation based on the principle of maximum ratio. From the data analysis, for the standard deviation of code DISB, the improvement of the method can up to 0·179 m with the poor quality data. In addition, compared to the parameter combination method, the standard deviation of all the phase DISB was deceased with the method in the paper. About the phase DISB of GPS L1/Galileo E1, the standard deviation decreased from 0·014/0·022/0·009/0·051 cycles to 0·006/0·015/0·004/0·029 cycles of four baselines, which represents the improvement of 57·14/31·82/55·56/43·14%. About the phase DISB of GPS L1/BDS B1, the standard deviation decreased from 0·014/0·061/0·010/0·052 cycles to 0·002/0·005/0·009/0·004 cycles of four baselines, which represents the improvement of 85·71/91·80/10·00/92·31%.

Keywords

GNSSTight CombinationDISBRatio
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 6 , November 2020 , pp. 1372 - 1386
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Copyright
Copyright © The Royal Institute of Navigation 2020

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References

REFERENCES

Euler, H. J. and Schaffrin, B. (1991). On a Measure of Discernibility Between Different Ambiguity Solutions in the Static-Kinematic GPS-Mode. In: Proceedings of the International Symposium on Kinematic Systems in Geodesy, Surveying, and Remote Sensing, Banff, Canada, September, 1990. Springer, New York, pp. 285–295.Google Scholar
Force, D. and Miller, J. (2013). Combined Global Navigation Satellite Systems in the Space Service Volume. In: Proceedings of the ION International Technical Meeting, San Diego, USAGoogle Scholar
Gao, W., Gao, C., Pan, S., et al. (2017). Inter-system differencing between GPS and BDS for medium-baseline RTK position. Remote Sensing. doi:10.3390/rs9090948CrossRefGoogle Scholar
Gao, W., Meng, X., Gao, C., et al. (2018). Combined GPS and BDS for single-frequency continuous RTK positioning through real-time estimation of differential inter-system biases. GPS Solutions, 22(1), 20.CrossRefGoogle Scholar
Julien, O., Alves, P., Cannon, M. E. and Zhang, W. (2003). A Tightly Coupled GPS/GALILEO Combination for Improved Ambiguity Resolution. In Proceedings of the ENC GNSS 2003, Graz, Austria, 22–25 April 2003.Google Scholar
Liu, H., Shu, B., Xu, L., Qian, C., Zhang, R. and Zhang, M. (2017). Accounting for inter-system bias in DGNSS positioning with GPS/GLONASS/BDS/Galileo. Journal of Navigation, 70, 686–698.CrossRefGoogle Scholar
Odijk, D. and Teunissen, P. (2013a). Characterization of between-receiver GPS-Galileo inter-system biases and their effect on mixed ambiguity resolution. GPS Solution, 17(4), 521–533.CrossRefGoogle Scholar
Odijk, D, Teunissen, PJG (2013b) Estimation of differential intersystem biases between the overlapping frequencies of GPS, Galileo, BeiDou and QZSS. Proc. 4th international colloquium scientific and fundamental aspects of the Galileo program, Prague, Czech Republic, December 4–6, 1–8.Google Scholar
Odijk, D., Nadarajah, N., Zaminpardaz, S. and Teunissen, P. J. G. (2016). GPS, Galileo. QZSS and IRNSS differential ISBs: Estimation and application. GPS Solution, 21, 439–450.CrossRefGoogle Scholar
Odolinski, R., Teunissen, P. and Odijk, D. (2014). Combined BDS, Galileo, QZSS and GPS single-frequency RTK. GPS Solution, 19(1), 151–163.CrossRefGoogle Scholar
Pan, S., Meng, X., Gao, W., Wang, S. and Dodson, A. (2014). A new approach for optimizing GNSS positioning performance in harsh observation environments. Journal of Navigation, 67, 1029–1048.CrossRefGoogle Scholar
Paziewski, J. and Wielgosz, P. (2015). Accounting for Galileo-GPS inter-system biases in precise satellite positioning. Journal of Geodesy, 89(1), 81–93.CrossRefGoogle Scholar
Tegedor, J., Øvstedal, O. and Vigen, E. (2014). Precise orbit determination and point positioning using GPS, Glonass, Galileo and BeiDou. Journal of Geodesy, 4, 65–73.Google Scholar
Teunissen, P. J. G. (1995). The least-squares ambiguity decorrelation adjustment: A method for fast GPS integer ambiguity estimation. Journal of Geodesy, 70, 65–82.CrossRefGoogle Scholar
Teunissen, P. and Kleusberg, A. (1996). GPS observation equations and positioning concepts. In: Kleusberg, A., Teunissen, P. (eds.). GPS for Geodesy. Springer. Berlin, 175–218.CrossRefGoogle Scholar
Teunissen, P. J. G., Odolinski, R. and Odijk, D. (2014). Instantaneous BeiDou + GPS RTK positioning with high cut-off elevation angles. Journal of Geodesy, 88, 335–350.10.1007/s00190-013-0686-4CrossRefGoogle Scholar
Tian, Y., Ge, M. and Neitzel, F. (2015). Particle filter-based estimation of inter-frequency phase bias for real-time GLONASS integer ambiguity resolution. Journal of Geodesy, 89(11), 1145–1158.CrossRefGoogle Scholar
Tian, Y., Ge, M., Neitzel, F., et al. (2017). Particle filter-based estimation of inter-system phase bias for real-time integer ambiguity resolution. GPS Solutions, 21(3), 949–961.CrossRefGoogle Scholar