9.2.1 Single-Session Network Processing

INTRODUCTION

There are, generally speaking, two classes of processing strategies for obtaining a GPS single session solution: Using a SINGLE BASELINE mode GPS data reduction, for some or all of the possible baseline combinations. Using a one-step GPS data reduction in the MULTI-BASELINE mode.

Single Baseline vs Multi-Baseline Solutions

A multi-baseline phase data reduction procedure accounts for the inherent correlation between stations observing simultaneously through the functional model for the double-differences (section 6.3.5) containing parameters linking independent baselines. For example, if baselines 1-2 and 2-3 are to be used to generate double-differences, then the coordinate parameters for station 2 appear in the parametric equations for both of the baselines 1-2 and 2-3, hence the baselines are functionally correlated. Further, if the between-station correlations are include in the weight matrix of the observations, the stochastic correlations between the differenced observations are also taken into account.

It must be stressed from the outset however that, in practice, there is often little discernible effect at the few parts per million level, on GPS solutions, between processing single baselines and processing all session observations in a simultaneous multi-baseline adjustment. However, such a statement must carry several riders:

• For example, multi-baseline solutions are theoretically superior with regard to ambiguity resolution for baselines of the order of tens of kilometres, than are single baseline solutions.
• High precision GPS geodesy, particularly for medium and long baselines, demands that all correlations are taken into account.

(With regard to the former, some discussion is given in this chapter. As far as GPS geodesy is concerned, this topic is beyond the scope of these notes and will not be dealt with further.)

The two approaches to GPS single session adjustment: (a) the single baseline processing of individual baselines, and (b) the one-step multi-baseline processing; are briefly discussed in this chapter. Although they may be viewed as being in many respects (competitive) alternatives for processing session data, the two approaches have strengths and weaknesses that can be used to advantage in certain applications. Some of these are summarised below.

Single Baseline Solutions:

• Permit close examination of the quality of a solution (for example, such aspects as cycle slip detection/repair, and outlier detection).
• Requires less sophisticated GPS data reduction software.
• The results are more easily visualised than in a multi-baseline adjustment.
• All baselines can be processed, not just the independent ones.
• Each session's results can be processed at the field office as the survey progresses, and the baseline results accumulated within the network program.
• This non-rigorous approach may furnish the final results (in the case of lower accuracy surveys), or alternatively, the entire dataset may be reprocessed in the office at the end of the campaign.

Multi-Baseline Solutions:

• The solution is mathematically rigorous.
• Requires suitable GPS data reduction software, however, most commercial GPS reduction software is not able to carry out a multi-baseline reduction.
• The element of "arbitrariness" is reduced, as there is no need to select independent baselines to process.
• Ambiguity resolution may be made easier (or at least more reliable) using the multi-baseline approach.
• Does not require secondary network adjustment software to combine the session solutions.
• May be more difficult to "trouble-shoot" problems such as bad data, antenna height errors, etc.

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© Chris Rizos, SNAP-UNSW, 1999