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Estimation and Mitigation of the Main Errors for Centimetre-level Compass RTK Solutions over Medium-Long Baselines

Published online by Cambridge University Press:  14 October 2011

Hairong Guo ,
Haibo He ,
Jinlong Li  and
Aibing Wang
Hairong Guo*
Affiliation:
(P.O. Box 5128, Beijing 100094, China)
Haibo He
Affiliation:
(P.O. Box 5128, Beijing 100094, China)
Jinlong Li
Affiliation:
(Institute of Surveying and Mapping of Information Engineering University, Zhengzhou, China)
Aibing Wang
Affiliation:
(P.O. Box 5128, Beijing 100094, China)
*
(Email: hairongguo@263.net)
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Abstract

Centimetre-level RTK solutions are mainly influenced by satellite orbit errors, ionospheric and tropospheric delays, and measurement noise (including multipath effects). Estimation and mitigation of the main errors for the CM-level Compass RTK solutions over medium-long baselines are investigated. Tests conducted for this research lead to the following conclusions:

  1. 1. For 100 km baselines, a 4 cm error in height component will be induced by a 10 m orbit error. For longer baselines, rapid precise ephemeris will be needed for CM-level accuracy RTK solutions.

  2. 2. The residual ionospheric delay error can be eliminated using the optimal triple-frequency ionosphere-free linear combination with the coefficients of 2·6087, −0·5175 and −1·0912 respectively for observations on f1, f2 and f3 frequencies. This combination is optimal in terms of its noise level, e.g., the noise is only amplified three times. It can be used for high accuracy RTK positioning.

  3. 3. The residual tropospheric delay can be resolved for the introduced relative zenith tropospheric delay (RZTD) parameters.

It is shown that the RTK solutions estimated from the least squares (LS) with the RZTD parameters are worse than that without these parameters. For instance, the errors in the height components are amplified approximately three times, which may be caused by the strong correlation between the introduced RZTD parameters and the height components. However, considering the fact that the residual zenith tropospheric delays vary slowly with time and the variation can be assumed to follow a random walk process, the RTK solutions can be improved using the Kalman filter and a priori information for the RZTD parameters.

Keywords

CompassMedium-long baselinesRTKRelative Zenith Tropospheric Delay (RZTD)
Type
Research Article
Information
The Journal of Navigation , Volume 64 , Supplement S1: Chinese Beidou and the Next Generation GNSS , November 2011 , pp. S113 - S126
Copyright
Copyright © The Royal Institute of Navigation 2011

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References

REFERENCES

Fan, J. J. and Wang, F. X. (2007). A Method for GNSS Three Frequency Ambiguity Resolution Based on Short Baseline. Acta Geodaetica et Cartographica Sinica, 36(1), 43–49 (in Chinese).Google Scholar
Feng, Y. M. (2008). GNSS Three Carrier Ambiguity Resolution using Ionosphere-reduced Virtual Signals. Journal of Geodesy, 82(12), 847–862.CrossRefGoogle Scholar
Feng, Y. M. and Li, B. F. (2008a). A Benefit of Multiple Carrier GNSS Signals: Regional Scale Network-based RTK with Doubled Inter-station Distances. Journal of Spatial Sciences, 53(2), 135–147.CrossRefGoogle Scholar
Feng, Y. M. and Li, B. F. (2008b). Three Carrier Ambiguity Resolutions: Generalized Problems, Models, Methods and Performance Analysis using Semi-generated Triple Frequency GPS Data. Proceedings of ION GNSS 2008, 2831–2840.Google Scholar
Feng, Y. M. and Rizos, C. (2009). Network-based Geometry-Free Three Carrier Ambiguity Resolution and Phase Bias Calibration. GPS Solutions, 13(1), 43–56.CrossRefGoogle Scholar
Feng, Y. M., Rizos, C. and Higgins, M. (2007). Multiple Carrier Ambiguity Resolution and Performance Benefits for RTK and PPP Positioning Services in Regional Areas. Proceedings of ION GNSS 2007, 668–678.Google Scholar
Guo, H. R., He, H. B. and Wang, A. B. (2010). The Method of Real-time GNSS Ambiguity Resolution for Short Baselines. China Satellite Navigation Conference 2010, 388. (in Chinese).Google Scholar
Han, S. W. and Rizos, C. (1999). The Impact of Two Additional Civilian GPS Frequencies on Ambiguity Resolutions Strategies. Proceedings of ION ATM 1999, 315–321.Google Scholar
Hatch, R. (2006). A New Three-frequency, Geometry-free Technique for Ambiguity Resolution. Proceedings of ION GNSS 2006, 309–316.Google Scholar
He, H. B., Guo, H. R. and Wang, A. B. (2010). Cycle Slip Recovery Method for Long-range Dual-frequency GPS Kinematic Surveying. Journal of Geomatics Science and Technology, 27(6), 396–398 (in Chinese).Google Scholar
Li, B. F. (2010). Theory and Method for Parameter and Variance-covariance Component Estimation in Mixed Integer Linear GPS Model. Tongji University. (in Chinese).Google Scholar
Li, J. R., Yang, Y. X., Xu, J. Y., He, H. B. and Guo, H. R. (2011). Real-time Cycle-Slip Detection and Repair Based Code/Phase Combination for Triple-Frequency GNSS Undifferenced Observation Data. Acta Geodaetica et Cartographica Sinica, in Press (in Chinese).Google Scholar
Teunissen, P., Joosten, P. and Tiberius, C. (2002). A Comparison of TCAR, CIR and LAMBDA GNSS Ambiguity Resolution. Proceedings of ION GPS 2002, 2799–2808.Google Scholar
Yang, Y. X., Gao, W. G. and Zhang, X. (2010). Robust Kalman Filtering with Constraints: A Case Study for Integrated Navigation. Journal of Geodesy, 2010(84), 373–381.CrossRefGoogle Scholar