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Deformation monitoring using GPS is usually carried out by installing and operating a local network of GPS receivers mounted on the deforming body, e.g. the flanks of a volcano.  For continuous monitoring applications a near-real-time, epoch-by-epoch solution obtained from multi-baseline processing is desired in order to take into account between-baseline correlations and to detect movements over as short a period of time as possible.  In the case of the volcano monitoring application, the sides of the volcano will block out part of the sky, hence the receivers are not likely to track a lot of satellites that are visible from all receiver stations at the same time.  If the usual base-station / base-satellite approach is used in the baseline processing, only the common satellites are considered, resulting in the number of possible double-differenced observables being comparatively low, hence a lot of valuable information may be lost.  The proposed method based on the work by Saalfeld (1999) considers satellites that are visible from a small number of network stations only.  Hence the number of independent double-differenced observables can be maximised in order to obtain a better solution.  A numerical example is given which verifies the improved solutions that can be obtained using this data processing approach

Optimizing the Number of Double-Differenced Observations for GPS Networks in Support of Deformation Monitoring Applications