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Low-cost, high-precision, single-frequency GPS–BDS RTK positioning

Abstract

The integration of the Chinese BDS with other systems, such as the American GPS, makes precise RTK positioning possible with low-cost receivers. We investigate the performance of low-cost ublox receivers, which cost a few hundred USDs, while making use of L1 GPS + B1 BDS data in Dunedin, New Zealand. Comparisons will be made to L1 + L2 GPS and survey-grade receivers which cost several thousand USDs. The least-squares variance component estimation procedure is used to determine the code and phase variances and covariances of the receivers and thus formulate a realistic stochastic model. Otherwise, the ambiguity resolution and hence positioning performance would deteriorate. For the same reasons, the existence of receiver-induced time correlation is also investigated. The low-cost RTK performance is then evaluated by formal and empirical ambiguity success rates and positioning precisions. It will be shown that the code and phase precision of the low-cost receivers can be significantly improved by using survey-grade antennas, since they have better signal reception and multipath suppression abilities in comparison with low-cost patch antennas. It will also be demonstrated that the low-cost receivers can achieve competitive ambiguity resolution and positioning performance to survey-grade dual-frequency GPS receivers.

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Acknowledgements

Ryan Cambridge and Callum Johns at School of Surveying, University of Otago, collected the ublox data. The second author is the recipient of an Australian Research Council (ARC) Federation Fellowship (Project Number FF0883188). All this support is gratefully acknowledged.

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Correspondence to Robert Odolinski.

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Odolinski, R., Teunissen, P.J.G. Low-cost, high-precision, single-frequency GPS–BDS RTK positioning. GPS Solut 21, 1315–1330 (2017). https://doi.org/10.1007/s10291-017-0613-x

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  • DOI: https://doi.org/10.1007/s10291-017-0613-x

Keywords

  • Low-cost receiver
  • Multi-GNSS
  • Real-time kinematic (RTK) positioning
  • Least-squares variance component estimation (LS-VCE)
  • Time correlation