Members of the VLBI2010 Committee have carried out a series of Monte Carlo simulations to assess the error contribution of tropospheric delays, clock errors, and observation noise to parameters estimated with geodetic VLBI, like baseline lengths, station coordinates, or Earth orientation parameters. VLBI2010 simulations have been performed by the Goddard group (with Calc/Solve and Geodyn) and by the Vienna group (in the beginning with the Occam Kalman filter and a dedicated Precise-Point-Positioning tool for VLBI simulations, and later on with the Vienna VLBI Software VieVS).
Figure 1 (from Pany et al. 2011): Workflow of the Monte Carlo simulations. Typically, 25 24h sessions have been simulated and consequently analyzed to determine bias and standard deviation of the 25 realizations. However, with more experience in simulations, one should rather create 50 realizations.
These studies have shown (e.g., Petrachenko et al. 2009, Pany et al. 2011; various IVS Memoranda) that deficiences in tropospheric delay modeling are the major error source for VLBI2010 among the three sources mentioned above. [It is important to note here, that we did not consider source structure effects for the simulations, nor did we simulate systematic effects.]
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Figure 1 (from Pany et al. 2011): a) median (over all stations) 3D position rms in mm versus structure constant Cn and b) versus effective height H. These two parameters, Cn and H, are the key quantities for the simulation of tropospheric delays according to Nilsson et al. (2007). c) median 3D position rms in mm versus Allan Standard Deviation (ASD) of the clocks and d) versus white noise added per observation. The simulations have been carried out for a 16-station network with the following default values: Cn = 1.0 x 10-7 m-1/3 , H = 2 km, wind 10 m/s towards East, ASD = 1 x 10-14 at 50 minutes, white noise = 4/sqrt(2) ps per baseline observation.
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A preliminary evaluation has also been carried out on the impact of the cutoff angle in VLBI observations. Tierno Ros et al. (2013) have taken a 16-station network and they have created schedules
Figure 3 (from Tierno Ros et al. 2013)
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