The Variometric Approach for Displacement Analysis Standalone Engine (VADASE) uses time-differenced carrier-phase measurements to estimate station velocity with mm-level accuracy using only broadcast satellite orbit and clock corrections. These velocity estimates are then integrated to derive station displacements at the centimeter level over short time intervals. These characteristics are well suited for earthquake monitoring since the method does not rely on external communication channels which are often among the first components to fail during an earthquake. But how does VADASE compare to a PPP solution?
The VADASE concepts were described in details by Colosimo et al. (2011), where the applicability of the approach was demonstrated using GPS data collected during recent earthquakes. This method was awarded the DLR Special Topic Prize on 18 October 2010 and the first European Satellite Navigation Competition Audience Award on 16 November 2010. It is patent pending and Leica has included it into their GR50 and GR30 GNSS receivers. Recently, modifications were made to VADASE to handle larger kinematic displacements and the method was re-branded Kin-VADASE (Branzanti et al. 2016).
VADASE is often perceived to be better suited to earthquake monitoring than PPP because:
It integrates precise velocity measurements into displacements, and is therefore not subject to the PPP convergence period
It relies on broadcast satellite orbit and clock corrections, available in real time without additional communication channels
Are these claims justified?
The first key concept to understand is that a PPP solution using carrier-phase observations has the same information content as a time-differenced solution. In other words, if we process only a few minutes of data using a kinematic PPP solution in a batch adjustment, the estimated displacement will be identical as the one obtained from a time-differenced solution. It is true that, since the PPP solution did not have time to converge, the estimated coordinates may be far from the true values, but the time variation of the position will be correct and precise velocity estimates could also be derived from these positions.
It is also possible to obtain precise displacements from a PPP solution without processing the data in a batch mode, as described in the previous paragraph. To get rid of the PPP convergence, we can simply fix the initial receiver position and clock parameters in the PPP filter (this will in turn lead to precise ambiguity estimates). The estimated position at subsequent epochs will thus give us the displacement with respect to the initial position. PPP with broadcast satellite orbit and clock corrections is also possible. Since these errors vary slowly over a short period of time, accurate displacements are still achievable over a few minutes.
In order to demonstrate how PPP can provide similar results as VADASE, I processed data from station P496 during the 2010 earthquake in California (this data set was also used in the Colosimo et al. paper). The figure below shows the PPP-derived displacements using only 3 minutes and 40 seconds of data and broadcast satellite orbit and clock corrections. In this case, the solution is smoothed to eliminate the convergence period. As you can see, the results are very close to the VADASE solution (refer to above paper, Fig. 8), but no trends were removed from the PPP solution.
Fig 1 Displacements of station P496 during the 4 April 2010 earthquake using PPP with broadcast satellite orbit and clock corrections
In summary, PPP can provide a similar level of performance as VADASE under the same constraints. In my opinion, a PPP solution using precise orbit and clock products is still a better alternative: if communication capabilities are maintained, a more precise solution can be obtained over a longer time interval. And if the real-time flow of corrections is lost, a linear prediction of satellite clock corrections over a short time interval will certainly not be worse than using broadcast corrections.
Branzanti M, Colosimo G, Mazzoni A (2016) Variometric approach for real-time GNSS navigation: first demonstration of Kin-VADASE capabilities. Adv Space Res doi: 10.1016/j.asr.2016.09.026
Colosimo G, Crespi M, Mazzoni A (2011) Real‐time GPS seismology with a stand‐alone receiver: A preliminary feasibility demonstration. J Geophysical Res doi:10.1029/2010JB007941