Lecture_7

• solve writes these in day dir
– or from SINEX files
• available from IGS • and soon for IVS for VLBI and ILS for SLR results
– Program detects file type • Or written by globk itself
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Stochastic processes
• Stochastic models in globk are random walks characterized by variance of change in process over an interval of time • Variance grows linearly with time (standard deviation grows as square root of time) • If proc classed as deterministic
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Preparing to run GLOBK
• Shell script sh_glred – automates standard runs with globk – useful to start – assumes internet access – but can be run without internet • Globk needs: – Binary h-files
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Defining a coordinate system with glorg
• The glorg module of GLOBK applies rotation, translation, and scale to best align estimated coordinates with prior values for a selected set of stations – this process is called “stabilization” (pos_org) – subset of stations is the “stabilization list” (use_site) • User chooses which parameters are free (estimated) – translation xrot yrot zrot – rotation xtran ytran ztran – scale • If scale is used, it should be explicitly estimated in globk
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running htoglb
• htoglb dir ephfile[options] file_list – dir is directory where binary files will be written – ephfile is satellite orbit file
GLOBK Theory and Solution Types
Kalman filtering Stochastic processes Applications
Summary of Use of GLOBK
• GAMIT output is an “h-” file of loosely constrained estimates and covariances, used as input (quasi-) observations to GLOBK • GAMIT ascii h-files converted to binary h-files for input to GLOBK • GLOBK combines h-files from several networks for a single day and h-files from multiple epochs to estimate positions in a time series or average velocities
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Motivation
• GLOBK is quicker than GAMIT – Typically perform many GLOBK runs to test different hypotheses and correct problems in original GAMIT analyses with out re-running GAMIT. • Ultimately once all is understood, GAMIT is rerun and the process repeated for the final results
– orientation (3 parameters) – scale (1 parameter)
• Theoretically, scale should be defined but systematic errors in the position of the phase center of satellites can cause a scale error
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Kalman Filtering
• Estimation method in which parameters can be random processes • Examples: – polar motion and UT1 – radiation pressure effects on satellites – coordinates after EQ • Nearly all parameters in GLOBK can be stochastic or deterministic • Statistical character set by commands – apr_XXX – mar_XXX
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Things GLOBK cannot do
• Remove non-linear effects – GLOBK assumes a linear model • Repair mistakes in original analysis – cycle slips – wrong antenna phase center models • resolve ambiguities – (would make files too large) • But GLOBK can delete sites – can help avoid contaminating solution
• written by htoglb from solve’s output
– A command file to tell it what to do
• e.g., globk.cmd
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Binary h-files
• Generated with htoglb – from the h<expt>a.<yy><doy> files
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Velocity origin
• Same approach can be applied to site velocities, i.e. rates of – translation – rotation – scale • Use rate_org command with same key words • This will align the estimated station velocities with prior values for (the same) set of selected sites • No specific station coordinates are tightly constrained • We call this “velocity stabilization” in jargon. • In papers we write, “velocities with respect to a set of stations on stable North America”
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GLOBK command files
• Example in ~/gg/templates/globk_comb.cmd • Basic features of command files – These are also common to other input files used by globk – Any non-blank character in column 1 denotes comment – Only minimum redundant part of command needed – In many cases, not all arguments need be given • Examine the command file from templates
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