Introduction To GAMIT/GLOBK - GeoWeb
1Introduction to GAMIT/GLOBKRelease 10.7T. A. Herring, R. W. King, M. A. Floyd, S. C. McClusky*Department of Earth, Atmospheric, and Planetary SciencesMassachusetts Institute of TechnologyContents1. GNSS Measurements and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 31.1 Phase and pseudorange observations . . . . . . . . . . . . . . . . . . . 31.2 Modeling the motions of satellites and stations . . . . . . . . . . . . 61.3 Parameter estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82. Automatic Processing with GAMIT and GLOBK . . . . . . . . . . . . . 102.1 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2 Summary of program flow . . . . . . . . . . . . . . . . . . . . . . . . . . . 132.3 Editing the control files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.4 Using sh gamit and sh glred . . . . . . . . . . . . . . . . . . . . . . . . 253. Evaluating Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304. Generating Time Series and Velocity Fields . . . . . . . . . . . . . . . . 344.1 Combining h-files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364.2 Data editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364.3 Weighting the data for realistic uncertainties . . . . . . . . . . . . . 374.4 Realizing a reference frame . . . . . . . . . . . . . . . . . . . . . . . . . . . 394.5 Generating time series and velocity solutions . . . . . . . . . . . . . 425. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44* Now at Australian National University2 June 2018
2PrefaceGAMIT/GLOBK is a comprehensive GNSS analysis package developed at MIT, theHarvard-Smithsonian Center for Astrophysics (CfA), Scripps Institution ofOceanography (SIO), and Australian National University for estimating stationcoordinates and velocities, stochastic or functional representations of post-seismicdeformation, atmospheric delays, satellite orbits, and Earth orientation parameters.Although the software is currently maintained by the three authors of this document atMIT, many people have made substantial contributions. The orbital integration andmodules used in computing the theoretical phase observable have their origins in thePlanetary Ephemeris Program (PEP) written by Michael Ash, Irwin Shapiro, and BillSmith at Lincoln Laboratory in the 1960’s, with later contributions by Bob Reasenbergand John Chandler at MIT. The codes for processing GPS observations were developedat MIT in the 1980’s by Chuck Counselman, Sergei Gourevitch, Yehuda Bock, RickAbbot, and King. GAMIT attained its current form through the efforts of Bock, DananDong, Peng Fang (SIO), Kurt Feigl, Herring, King, McClusky (ANU), Mike Moore(ANU), Peter Morgan (Canberra U), Mark Murray (NM Tech), Liz Petrie (U Newcastle),Berkhard Schraffin (Ohio State), Seiichi Shimada (NEID), Paul Tregoning (ANU), andChris Watson (U Hobart). GLOBK was developed by Herring and Jim Davis at CfA forcombination of VLBI data and modified at MIT to incorporate GPS data. Details of thesecontributions may be found in the references listed at the end of this manual. Funding forthe early development of GAMIT was provided by the Air Force Geophysics Laboratory,and for GLOBK by NASA. Current support for development and support of thescientific community comes primarily from the National Science Foundation.To control processing the software uses C-shell scripts (stored in /com and mostly namedto begin with sh ) which invoke the Fortran or C programs compiled in the /libraries,/gamit, and /kf directories. The software is designed to run under any UNIX operatingsystem supporting X-Windows, including LINUX and MacOS. The parameter logicallows a maximum of 99 sites and the standard distribution is dimensioned for 80 sites,but since the run is proportional to the cube of the number of parameters, with networkslarger than 50 sites greater efficiency is obtained by parallel processing using connectedsubnets. IGS processing at MIT includes over 300 sites, and processing at New MexicoTech for the North American Plate Boundary Observatory over 1000 sites.The first chapter of this manual provides some theoretical background for readers notfamiliar with high-precision GNSS analysis. Chapter 2 describes the setup of tables andcommands for automatic processing to obtain time series of daily position estimates, andChapter 3 provides a guide to evaluating your results. In Chapter 4 we discuss variousapproaches to generating time series and estimating station velocities from observationsspanning several years. More detailed documentation is available in the longer GAMITReference Manual and GLOBK Reference Manual. There are also tutorials available online at http://www-gpsg.mit.edu. The most up-to-date information about the commandsis available through help files, invoked by typing the name of the shell-script or programwithout arguments.2 June 2018
31. GNSS Measurements and Analysis1.1 Phase and pseudorange observationsHigh-precision geodetic measurements with GNSS are performed using the carrier beatphase, the output from a single phase-tracking channel of a GNSS receiver. Thisobservable is the difference between the phase of the carrier wave implicit in the signalreceived from the satellite, and the phase of a local oscillator within the receiver. Thephase can be measured with sufficient precision that the instrumental resolution is amillimeter or less in equivalent path length. The dominant source of error in a phasemeasurement or series of measurements between a single satellite and ground station isthe unpredictable behavior of the time and frequency standards ("clocks") serving asreference for the transmitter and receiver. Even though the satellites carry atomicfrequency standards, the instability of these standards would still limit positioning to theseveral meter level were it not for the possibility of eliminating their effect through signaldifferencing.A second type of GNSS measurement is the pseudo-range, obtained using the codestransmitted by the satellites. Pseudo-ranges provide the primary GNSS observation fornavigation but are not precise enough to be used directly in geodetic surveys. They areuseful, however, for estimating the offsets of receiver clocks, resolving ambiguities, andrepairing cycle slips in phase observations.For a single satellite, differencing the phases (or pseudo-ranges) of signals receivedsimultaneously at each of two ground stations eliminates the effect of bias andinstabilities in the satellite clock. This measurement is commonly called the betweenstations-difference, or single-difference observable. Forming a second difference,between satellites, eliminates the effect of bias and instabilities in the station blocks.Since the phase biases of the satellite and receiver oscillators at the initial epoch areeliminated in doubly differenced observations, the doubly differenced range (in phaseunits) is the measured phase plus an integer number of cycles. (One cycle has awavelength of 19 cm at GPS L1 and 24 cm at GPS L2 for code-correlating receivers; halfthese values for squaring-type receivers used prior to the mid-1990s, and slightlydifferent values for the primary frequencies transmitted by Glonass, Beidou, and Galileo.In the manuals we will use the term “L1” to refer to the higher and “L2 the lower of thetwo L-band frequencies though these may be, e.g. for Galileo E1(L1) and E5.) If themeasurement errors, arising from errors in the models for the orbits and propagationmedium as well as receiver noise, are small compared to a cycle, there is the possibilityof determining the integer values of the biases, thereby obtaining from the initiallyambiguous doubly differenced phase an unambiguous measure of doubly differencedrange. Resolution of the phase ambiguities improves the uncertainties in relative positionmeasures by about a factor of 1.5 for 24-hr sessions, 3 for 8-hr sessions and more than 5for short sessions. (see, e.g., Blewitt [1989], Dong and Bock [1989] ).2 June 2018
4GAMIT incorporates difference-operator algorithms that map the carrier beat phases intosingly and doubly differenced phases. These algorithms extract the maximum relativepositioning information from the phase data regardless of the number of data outages, andtake into account the correlations that are introduced in the differencing process. (SeeBock et al. [1986] and Schaffrin and Bock[1988] for a detailed discussion of thesealgorithms.) An alternative, (nearly) mathematically equivalent approach to processingGNSS phase data is to use formally the (one-way) carrier beat phases but estimate at eachepoch the phase offset due to the station and satellite clocks. This approach is used bythe autcln program in GAMIT to compute one-way phase residuals for editing, display,and estimating atmospheric and ionospheric slant delays.In order to provide the maximum sensitivity to geometric parameters, the carrier phasemust be tracked continuously throughout an observing session. If there is an interruptionof the signal, causing a loss of lock in the receiver, the phase will exhibit a discontinuityof an integer number of cycles (“cycle-slip”). This discontinuity may be only a fewcycles due to a low signal-to-noise ratio, or it may be thousands of cycles, as can occurwhen the satellite is obstructed at the receiver site. Initial processing of phase data isoften performed using time differences of doubly differenced phase ("triple differences",or "Doppler" observations) in order to obtain a preliminary estimate of station or orbitalparameters in the presence of cycle slips. The GAMIT software uses triple differences inediting but not in parameter estimation. Rather, it allows estimation of extra biasparameters whenever the automatic editor has flagged an epoch as a cycle slip that cannotbe repaired. Various algorithms to detect and repair cycle slips are described by Blewitt[1990], and also in Chapter 4 of the GAMIT Reference Manual.Although phase variations of the satellite and receiver oscillators effectively cancel indoubly differenced observations, errors in the time of the observations, as recorded by thereceiver clocks, do not. However, the pseudo-range measurements, together withreasonable a priori knowledge of the station coordinates and satellite position, can beused to determine the offset of the station clock to within a microsecond, adequate tokeep errors in the doubly differenced phase observations below 1 mm.A major source of error in single-frequency GNSS measurements is the variable delayintroduced by the ionosphere. For day-time observations near solar maximum this effectcan exceed several parts per million of the baseline length. Fortunately, the ionosphericdelay is dispersive and can usually be reduced to a millimeter or less by forming aparticular linear combination (LC) of the L1 and L2 phase measurements:φ LC 2.546 φ L1 1.984 φ L2(1)for GPS (see, e.g., Bock et al. [1986], or Dong and Bock [1989].)Forming LC,however, magnifies the effect of other error sources. For baselines less than a fewkilometers the ionospheric errors largely cancel, and it is preferable to treat L1 and L2 astwo independent observables rather than form the linear combination. The stationseparation at which the ionospheric errors exceed the phase noise depends on many2 June 2018
5factors (receiver, antenna, multipath environment, latitude, time of day, sunspot activity)and must be determined empirically by analyzing the data with both observable types.In examining phase data for cycle slips, it is often useful to plot several combinations ofthe L1 and L2 residuals. Single-cycle slips in GPS L1 or L2 will appear as jumps of2.546 or 1.984 cycles, respectively, in LC. Single-cycle slips in both GPS L1 and L2 (amore common occurrence) appear as jumps of 0.562 cycles in LC, which, thoughsmaller, may be more evident than the jumps in L1 and L2 because the ionosphere hasbeen eliminated. If the L2 phase is tracked using codeless techniques, the carrier signalrecorded by the receiver is at twice the L2 frequency, leading to half-cycle jumps when itis combined with full-wavelength data. Hence, a jump of a "single" L2 cycle will appearas 0.992 in LC, and simultaneous jumps in (undoubled) L1 and (doubled) L2 will appearas 1.554 cycles in LC. Another useful combination is the difference between L2 and L1with both expressed in distance unitsφ LG φ L2 0.779 φ L1(2)for GPS, called "LG" because the L2 phase is scaled by the "gear" ratio (f2/f1 60/77 1227.6/1575.42 for GPS). In the LG phase all geometrical and other non-dispersivedelays (e.g., the troposphere) cancel, so that we have a direct measure of the ionosphericvariations. One-cycle slips in L1 and L2 are difficult to detect in the LG phase in thepresence of much ionospheric noise since they are equivalent for GPS to only 0.221 LGcycles.If precise (P-code) pseudorange is available for both GNSS frequencies, then a "widelane" (WL) combination of L1, L2, P1, and P2 can be formed which is free of bothionospheric and geometric effects and is simply the difference in the integer ambiguitiesfor L1 and L2:WL n2 - n1 φ L2 φ L1 (P1 P2 ) (f1 - f2)/(f1 f2)(3)The WL observable can be used to fix cycle slips in one-way data [Blewitt, 1990] butshould be combined with LG and doubly differenced LC to rule out slips of an equalnumber of cycles at L1 and L2.These various combinations of phase and pseudorange observations are used not only indata editing, but also in resolving the phase ambiguities. When the LC observable isused, we determine the L1 and L2 ambiguities by first resolving n2 - n1 (“widelane”)and then n1 (“narrow lane”). If precise and unbiased pseudoranges are available, thewidelane ambiguities can be resolved for baselines up to thousands of kilometers underany ionosphere conditions. For measurements prior to 1995, and possibly prior to 2000,inter-channel receiver biases can corrupt the pseudoranges and it is necessary to use thephase observations alone with a constraint on the ionopshere to resolve the widelaneambiguities (see, e.g., Blewitt, 1989; Dong and Bock, 1989; Feigl et al., 1993]. GAMITgives you the option of selecting the method to be used, either pseudoranges (LC AUTCLN)or ionospheric constraints (LC HELP). When using the pseudorange approach with2 June 2018
6different receiver types, it is important to use the satellite-dependent differential codebiases (DCBs) computed from tracking data by the Center for Orbit Determination inEurope (CODE) [http://www.aiub.unibe.ch/ionosphere.html] and updated monthly at MIT in filedcb.dat. Once the wide-lane ambiguity for a given doubly differenced combination hasbeen resolved, resolving the narrow-lane ambiguity for that combination depends on thelevel of noise from the receiver, multipathing, and the troposphere, and the accuracy ofthe models employed for the position and motion of the stations and satellites. It isgenerally more difficult to resolve these ambiguities for the longest baselines, but for dataacquired since 2000 we can usually resolve 80-95% of the ambiguities in a globalanalysis.Although GAMIT can process data from single-frequency receivers, ionsopheric errorsbegin to limit relative positioning accuracy for station separations greater than 100-2000m, depending on time of day, latitude, and the solar sunspot cycle. So for mostapplications, the use of two frequencies is required to remove first-order ionsosphericeffects. Although some GNSS satellites transmit signals on three of more frequencies,GAMIT is currently limited to using only two. GAMIT is also limited to processing datafrom only one GNSS at a time, though the GAMIT position estimates from several GNSStracked during a session can easily be combined in GLOBK.1.2 Modeling the motions of the satellites and stationsA first requirement of any GNSS geodetic experiment is an accurate model of thesatellites' motion. The (3-dimensional) accuracy of the estimated baseline, as a fractionof its length, is roughly equal to the fractional accuracy of the orbital ephemerides used inthe analysis. The accuracy of the navigation (“broadcast”) orbit computed by the GNSScontrol centers using pseudorange measurements from 15 tracking stations is typically1-5 parts in 107 (2-10 m), well within the navigation design specifications for the systembut not accurate enough for the study of crustal deformation. By using phasemeasurements from a global network of over 100 stations, however, the InternationalGNSS Service (IGS) [Beutler et al., 1994a], is able to determine the satellites' motionwith an accuracy of 1 part in 109 (2 cm; 5-20 cm in earlier years; see http://acc.igs.org)For GPS surveys prior to 1994, the global tracking network was much smaller but canstill be used to achieve accurate results for regional surveys. If we estimate orbitalparameters and include in our analysis observations from widely separated stations whosecoordinates are well known, the fractional accuracy of the baselines formed by thesestations is transferred through the orbits to the baselines of a regional network. Forexample, a 10 mm uncertainty in the relative position of sites 2500 km apart introducesan uncertainty of only 1 mm in the components of a 250 km baseline. This scheme canbe used successfully even with regional fiducial stations, transferring, for example, therelative accuracy of 250-500 km baselines to a network less than 100 km in extent, ahelpful approach with surveys conducted prior to the availability of precise global orbits.The motion of a satellite can be described, in general, by a set of six initial conditions(Cartesian position and velocity, or osculating Keplerian elements, for example) and amodel for the forces acting on the satellite over the span of its trajectory. To model2 June 2018
7accurately the motion, we require knowledge of the acceleration induced by thegravitational attraction of the Sun, Moon, higher order terms in the Earth's static gravityfield, solid-Earth and ocean tides, and some means to account for the action of nongravitational forces due to direct solar radiation pressure, radiation reflected from theEarth, radiation emitted by the spacecraft’s radio transmission, and gas emission by thespacecraft's batteries and attitude-control system. For all GNSS satellites nongravitational forces are the most difficult to model and have been the source ofconsiderable research over the past 20 years (see Colombo [1986], Beutler et al. [1994b],and Ziebart et al. [2002] for more discussion).In principle, a trajectory can be generated either by analytical expressions or bynumerical integration of the equations of motion; in practice, numerical integration isalmost always used, for both accuracy and convenience. The position of the satellite as afunction of time is then read from a table (ephemeris) generated by the numericalintegration. In GAMIT the integration is performed by program arc using equationsgiven by Ash [1972].Besides the orbital motion of a satellite, we must take into account meter-level offsetsbetween its center of mass and the phase-center of the transmitting antenna, includingtemporary excursions of several decimeters lasting up to a half-hour during themaneuvers the satellites execute to keep their solar panels facing the Sun when the orbitalplane is nearly aligned with the Earth-Sun direction. For the satellites in each orbitalplane, this alignment occurs for several weeks twice a year, the so-called "eclipseseason". Yoaz Bar-Sever and colleagues at JPL have spent considerable effortdeveloping models of the satellites' orientation, even to point of making the behaviormore predictable by getting the US Defense Department to apply a small bias about theyaw axis to GPS satellites—a change that was implemented gr
and must be determined empirically by analyzing the data with both observable types. In examining phase data for cycle slips, it is often useful to plot several combinations of the L1 and L2 residuals. Single-cycle slips in GPS L1 or L2 will appear as jumps of 2.546 or 1.984 cycles, respectively, in LC. Single-cycle slips in both GPS L1 and L2 (a
May 21, 2021 · Massachusetts Institute of Technology, Cambridge, MA, USA *Now at Geoscience Australia, Canberra, Australia 1 Introduction This Quick Start Guide provides basic instructions for first-time users getting started with GAMIT/GLOBK. We describe the download, compilation and test processes, beyond which we
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