Integer ambiguity resolution in precise point positioning: method comparison

By Jianghui Geng, Xiaolin Meng, Alan H. Dodson, Felix Norman Teferle. 2010

279 citations recorded by the source corpus.

Integer ambiguity resolution at a single receiver can be implemented by applying improved satellite products where the fractional-cycle biases (FCBs) have been separated from the integer ambiguities in a network solution. One method to achieve these products is to estimate the FCBs by averaging the fractional parts of the float ambiguity estimates, and the other is to estimate the integer-recovery clocks by fixing the undifferenced ambiguities to integers in advance. In this paper, we theoretically prove the equivalence of the ambiguity-fixed position estimates derived from these two methods by assuming that the FCBs are hardware-dependent and only they are assimilated into the clocks and ambiguities. To verify this equivalence, we implement both methods in the Position and Navigation Data Analyst software to process 1 year of GPS data from a global network of about 350 stations. The mean biases between all daily position estimates derived from these two methods are only 0.2, 0.1 and 0.0 mm, whereas the standard deviations of all position differences are only 1.3, 0.8 and 2.0 mm for the East, North and Up components, respectively. Moreover, the differences of the position repeatabilities are below 0.2 mm on average for all three components. The RMS of the position estimates minus those from the International GNSS Service weekly solutions for the former method differs by below 0.1 mm on average for each component from that for the latter method. Therefore, considering the recognized millimeter-level precision of current GPS-derived daily positions, these statistics empirically demonstrate the theoretical equivalence of the ambiguity-fixed position estimates derived from these two methods. In practice, we note that the former method is compatible with current official clock-generation methods, whereas the latter method is not, but can potentially lead to slightly better positioning quality.

Subfields: Aerospace Engineering, Atomic and Molecular Physics, and Optics, Oceanography

View Paper: https://www.semanticscholar.org/paper/5a3619fa10fea745b4377e9fe7294d3300dc14be

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In Aerospace Engineering

  1. Yidong Lou
  2. Jing-nan Liu
  3. Chuang Shi
  4. Dezhong Chen
  5. Weiwei Song
  6. Polona Pavlovčič Prešeren
  7. Amir Khodabandeh
  8. Peter Teunissen

In Atomic and Molecular Physics, and Optics

  1. Yidong Lou
  2. Jing-nan Liu
  3. Chuang Shi
  4. Polona Pavlovčič Prešeren
  5. Amir Khodabandeh
  6. Peter Teunissen
  7. Bojan Stopar
  8. Oskar Sterle

In Oceanography

  1. Jing-nan Liu
  2. Dezhong Chen
  3. Weiwei Song
  4. Polona Pavlovčič Prešeren
  5. Amir Khodabandeh
  6. Peter Teunissen
  7. Bojan Stopar
  8. Oskar Sterle

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