8.1.8 GPS Baseline Processing

HOW GOOD IS THE SOLUTION?

There a re a number of "Quality Indicators" that may be monitored, including:

• RMS of observation residuals.
• Number of rejected observations.
• Statistical tests on residuals or parameters.
• Aposteriori variance factor.
• VCV matrix of solution.
• The type of "optimal" solution obtained.
• "Trustworthiness" of solution.
• Measures of reliability of selected ambiguity parameter set.

The following comments may be made with respect to the "RMS of residuals" and "rejected observations":

• A "low" RMS value and a "low" number of rejected observations often indicates that both the data and solution quality are OK.
• Manufacturers often give recommended maximum values of RMS. Generally a function of baseline length, observation type (L1, L2, L3), etc.
• In general, an RMS value below 0.1 cycles is considered acceptable.
• Data editing is often carried out during solution iterations. Generally based on some factor (say 3) x RMS.
• Possible reasons for high RMS and data rejection rates are the presence of multipath and uncorrected cycle slips. Residual plots are good tools to verify this.
• Some phase data processing software permits the residuals to be plotted. Residuals should be examined.

The following comments may be made with respect to the "statistical tests" and "VCV information":

• In general, little statistical testing is carried out on parameters or residuals.
• If the aposteriori variance factor is unity then it is likely that the VCV matrix has been adaptively scaled to ensure this happens.
• In general however, the output VCV matrix is too optimistic , suggesting higher precisions for the parameters than is warranted. Does not take into account unmodelled systematic biases (atmospheric refraction, satellite orbit and fixed station errors, etc.).
• The standard deviations of baseline components vary considerably as a function of the type of phase solution (triple-difference, double-difference ambiguity-free, double-difference ambiguity-fixed).

There are other several Quality Indicators related to "solution characteristics", including:

• What is the "optimal" solution? Was an ambiguity-fixed solution obtained? Was it expected?
• If an ambiguity-fixed solution was obtained, check the absolute and relative RMS of the residuals. Are resolved ambiguities reliable?
• If an ambiguity-fixed solution was obtained, check baseline components. Did baseline solution change by more than 10cm compared to the ambiguity-free solution?
• The formal accuracy estimates for the vertical component is usually twice the size of the horizontal components.
• Verify solution characteristics such as:
  • satellites used --> any health problems?
  • sample data rate
  • common tracking period --> as planned?
  • apriori station coordinates --> were the correct WGS84 values used?
  • antenna heights
  • elevation mask angle
  • troposphere reduction applied?
  • satellite geometry indicator --> PDOP, RDOP, etc.

Advantage can also be taken of "external evidence", including:

• Hierarchy of solutions --> Comparison of triple-difference and double-difference solutions.
  • "decimetre" triple-difference solution precisions
  • "centimetre" double-difference ambiguity-free solution precisions
  • "millimetre" double-difference ambiguity-fixed solution precisions
• Dual-frequency solutions -->Comparison of L1, L2 and L3 solutions.
• Single baseline vs multi-baseline solutions -->Different analysts? Process using different software packages?
• Repeat baseline solutions from different sessions.
• Solutions involving tracking to 4 or more satellites, over a period of 30-60 minutes, for baselines less than about 15km, should be high quality ambiguity-fixed solutions.
• Compare with ground control -->Usually just distance.
• Check BBS or Integrity Monitoring Service.

How does one really estimate the quality of individual solutions?   Combine the baselines into a network adjustment !

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