Bernese GPS Software Version 5.0 - Bernese GNSS Software

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6. Data Preprocessing 6.6.2 Generating Residual Statistic (RESRMS) Program RESRMS (”Menu>Service>Residual files>Generate residual statistics”) analyzes a set of selected residual files. It provides statistical information about the residuals, and writes optionally the following output files: • A summary file (default extension .SUM) gives a compact overview of the residual’s RMS per station or baseline and per satellite. • A histogram of the residuals for each station or baseline may be stored in another file (default extension .LST). • The edit information file (default extension .EDT) contains the list of observations identified as outliers. • Station observation sigma factors for the station weighting (default extension SOS) may be derived from the residuals. The program output of RESRMS provides statistical information for the residuals of the stations or baselines. An example is given in Figure 6.5. The stations or baselines are identified by their names, the measurement type (ObsTyp), and the session (Session) – some of these columns are not shown in the example above. For each station or baseline one line of program output is providing: Total RMS: the total RMS for all satellites, med.Resi : the median of all residuals (first a median of the residuals from all satellites is computed per epoch, the reported value is the median of this value from all epochs), Sigma : the width of the histogram (see options “OPTIONS FOR RESIDUAL HISTOGRAM” in panel “RESRMS 3: Residual Statistics and Sigma Factors”) containing two third of all observations (The option “Bin width for histogram” has a direct impact on the accuracy of this value.), numObs : the number of observations, FILE INFORMATION AND STATISTIC: ------------------------------ Num Station 1 Station 2 Total RMS med.Resi Sigma numObs nSat nDel ... --------------------------------------------------------------------------------------------- ... 1 BRUS 13101M004 FFMJ 14279M001 1.6 0.8 1.3 3426 28 19 ... 2 BRUS 13101M004 ONSA 10402M004 1.1 0.7 0.9 3588 28 5 ... 3 BRUS 13101M004 ZIMM 14001M004 1.2 0.7 1.0 3509 28 5 ... 4 FFMJ 14279M001 ZIMJ 14001M006 1.5 0.8 1.3 3462 37 11 ... 5 MATE 12734M008 ZIMJ 14001M006 1.2 0.7 1.0 3329 28 3 ... 6 PTBB 14234M001 ZIMM 14001M004 1.3 0.8 1.1 3294 28 5 ... 7 VILL 13406M001 ZIMM 14001M004 1.1 0.7 0.9 3460 29 3 ... --------------------------------------------------------------------------------------------- ... Figure 6.5: Example for a program output from RESRMS. Page 132 AIUB
nSat : the number of satellites, and 6.6 Screening of Post-Fit Residuals nDel : the number of observation pieces rejected based on the thresholds specified in options “DETECT LARGE RESIDUALS” in panel “RESRMS 2: Options” and added to the edit information file. The units for the residuals in program RESRMS is in general millimeters. The residuals for code measurements are re-scaled with respect to the residuals of phase measurements using a factor of 100 (specified in the file ${X}/GEN/CONST.), i.e., the units for code residuals are decimeters. All other weights applied in the parameter estimation process when computing the residuals (e.g., “Elevation-dependent weighting”, or “Station sigma factors” in program GPSEST) cannot be taken into account in program RESRMS. It is strongly recommended to save normalized residuals in GPSEST to assure a reliable and homogeneous outlier detection by RESRMS. Normalized residuals are defined as r norm = r/σr where r is the real residual and σr is the a priori (NORM APR) or the a posteriori (NORMALIZED for (option “Type of computed residuals” in panel “GPSEST 3.1: General Options 1”) RMS of the residual (see Section 7.4.4). In contrast to real residuals, normalized residuals are always converted to one-way L1 carrier phase residuals. One of the major purposes of the program RESRMS is the screening of post-fit residuals. The residual file from a GPSEST solution is analyzed for outliers and an edit information file (description in Section 22.10.7) is written. Using this file program SATMRK (description in Section 6.7.1) can mark the corresponding measurements in the observation files. These steps are highly recommended when processing baseline files and are mandatory when processing zero-difference observation files. When the observation files are preprocessed by the program RNXSMT (zero-difference case) the screening of the post-fit residuals should be done iteratively with lowering the outlier detection thresholds (option “DETECT LARGE RESIDUALS”). Station Observation Sigma Factors For each individual station a measurement noise may be computed from the residuals of their observations. Station observation sigma factors are then derived from this measurement noise. The conversion of measurement noise to sigma factors may be defined by the options “STATION OBSERVATION SIGMA FACTORS” in panel “RESRMS 3: Residual Statistics and Sigma Factors”. The station sigma factors may be stored in a file which is described in Section 22.8.14. The purpose of these station observation sigma factors is the following: As the noise of original code observations (not smoothed by program RNXSMT) may differ significantly for different receivers the sigma factors may be used for weighting the code observations in the parameter estimation or for rescaling the outlier rejection thresholds in program CODSPP. Station sigma factors are not necessary when processing phase observations. A file containing normalized residuals which were generated in GPSEST using a station observation sigma file already applied cannot be use to generate a new station sigma file. Bernese GPS Software Version 5.0 Page 133
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Bernese GPS Software Version 5.0 Ed
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Bernese GPS Software Version 5.0 As
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Contents 2.3.6.1 Ionosphere-Free Li
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Contents 6.3.3 Kinematic Stations .
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Contents 9.4.4 Pre-Elimination Opti
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Contents 13.2 How to Correct P1-P2
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Contents 18.3.2 Command Bar . . . .
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Contents 20.4 Description of the Pr
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Contents 22.8.2 Station Abbreviatio
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Contents Page XVI AIUB
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List of Figures 5.1 Flow diagram of
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List of Figures 13.3 P1-C1 code bia
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List of Figures 22.20 Tabular orbit
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List of Tables 12.2 Influences of t
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1. Introduction and Overview • bu
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1. Introduction and Overview Table
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1. Introduction and Overview • Th
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1. Introduction and Overview The Be
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1. Introduction and Overview for Ca
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2. Fundamentals 2.1.1 GPS System De
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2. Fundamentals Table 2.2: Componen
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2. Fundamentals Clock correction [n
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2. Fundamentals Figure 2.5: GLONASS
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2. Fundamentals Table 2.6: GLONASS
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2. Fundamentals In contrast to the
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2. Fundamentals 2.2 GNSS Satellite
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2. Fundamentals 2.2.2.1 The Kepleri
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2. Fundamentals Table 2.9: Perturbi
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2. Fundamentals R.A. of Ascending N
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2. Fundamentals where aROCK is the
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2. Fundamentals By taking the deriv
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2. Fundamentals δi error of satell
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2. Fundamentals Ionospheric refract
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2. Fundamentals 2.3.6.1 Ionosphere-
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2. Fundamentals Table 2.10: Linear
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3. Campaign Setup variable to the f
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3. Campaign Setup Figure 3.1: Examp
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3. Campaign Setup In this section w
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3. Campaign Setup 3.5 Processing Ov
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4. Import and Export of External Fi
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8. Initial Phase Ambiguities and Am
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9. Combination of Solutions 9.2 Seq
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9. Combination of Solutions Substit
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9. Combination of Solutions We may
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9. Combination of Solutions files a
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9. Combination of Solutions x x 1 t
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9. Combination of Solutions Both re
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9. Combination of Solutions 9.4 The
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9. Combination of Solutions 9.4.2 G
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9. Combination of Solutions Excepti
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9. Combination of Solutions As alre
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9. Combination of Solutions Table 9
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9. Combination of Solutions The poi
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9. Combination of Solutions (2) Tra
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9. Combination of Solutions Step 1:
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10. Station Coordinates and Velocit
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11. Troposphere Modeling and Estima
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12. Ionosphere Modeling and Estimat
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13. Differential Code Biases Promin
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13. Differential Code Biases Figure
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13. Differential Code Biases ======
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13. Differential Code Biases Page 2
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14. Clock Estimation τ (BRUS-PTBB)
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14. Clock Estimation Here the limit
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14. Clock Estimation to zero. All c
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14. Clock Estimation #OBS : Number
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14. Clock Estimation 14.3 Clock RIN
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14. Clock Estimation cessed if CCRN
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14. Clock Estimation RINEX files th
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14. Clock Estimation the clock valu
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14. Clock Estimation SINGLE POINT P
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15. Estimation of Satellite Orbits
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16. Antenna Phase Center Offsets an
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17. Data Simulation Tool GPSSIM 17.
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17. Data Simulation Tool GPSSIM The
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17. Data Simulation Tool GPSSIM The
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17. Data Simulation Tool GPSSIM Res
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18. The Menu System 18.2 Starting t
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18. The Menu System 18.3.1 Menu Bar
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18. The Menu System 18.3.5 Panel Co
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18. The Menu System the menu the ne
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18. The Menu System Table 18.1: Pre
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18. The Menu System 18.5.3 System E
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18. The Menu System 18.7 Change Opt
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18. The Menu System 18.9 Technical
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18. The Menu System ... ! Environme
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18. The Menu System The keyword ENV
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18. The Menu System ! List of Remai
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18. The Menu System The MENUAUX-mec
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18. The Menu System Keyword values
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19. Bernese Processing Engine (BPE)
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20. Processing Examples inspect the
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20. Processing Examples 20.3.1 How
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20. Processing Examples • (option
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20. Processing Examples PID 111 PRE
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20. Processing Examples 20.4.1.7 Cr
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20. Processing Examples 20.4.2.1 Co
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20. Processing Examples appears in
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20. Processing Examples PID 313 MPR
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20. Processing Examples Further rea
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20. Processing Examples # # Create
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20. Processing Examples PID 101 GPS
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20. Processing Examples The RINEX n
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20. Processing Examples # # Preproc
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20. Processing Examples the loop, d
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20. Processing Examples PID 903 CLK
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20. Processing Examples and IGS 00B
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20. Processing Examples • Save th
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20. Processing Examples PID 321 GPS
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20. Processing Examples PID 301 CLK
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21. Program Structure $C / %C% PGM
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21. Program Structure (program GPSE
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21. Program Structure continued fro
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21. Program Structure ! -----------
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22. Data Structure "Program" Area $
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22. Data Structure Table 22.1: List
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22. Data Structure 22.4.2 Geodetic
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22. Data Structure 22.4.4 Antenna P
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Page 484 AIUB ANTENNA PHASE CENTER
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22. Data Structure 22.4.5 Satellite
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22. Data Structure 22.4.6 Satellite
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22. Data Structure DIFFERENCE OF GP
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22. Data Structure 22.4.9 Subdaily
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22. Data Structure EGM96 EGM96, VER
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22. Data Structure SINEX : OPTION I
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22. Data Structure 22.4.16 Panel Up
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22. Data Structure 22.6.2 Header an
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22. Data Structure 15 Antenna type(
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22. Data Structure SVN-NUMBER= 2 ME
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22. Data Structure -1 2 1 5 TITLE :
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22. Data Structure Used by: ORBGEN
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22. Data Structure 53064.00 53065.0
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22. Data Structure CODE’S MONTHLY
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22. Data Structure Table 22.4: Stat
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22. Data Structure (3) TYPE 003: HA
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22. Data Structure 22.8.4 Station P
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22. Data Structure Remarks: • Eac
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22. Data Structure The following st
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22. Data Structure Table 22.7: List
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22. Data Structure AJAC $$ FES2004
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22. Data Structure Station sigma fi
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22. Data Structure GOPE 11502M002 Z
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22. Data Structure 22.8.18 Receiver
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22. Data Structure CODE RAPID 3-DAY
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22. Data Structure 22.9.3 Meteo and
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22. Data Structure IONOSPHERE MODEL
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22. Data Structure 22.10 Miscellane
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22. Data Structure 22.10.4 Variance
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22. Data Structure 22.10.5 Normal E
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22. Data Structure 22.10.7 Observat
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22. Data Structure Created by: Each
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22. Data Structure ----------------
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22. Data Structure 22.10.17 BPE log
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23. Installation Guide 23.1.2 Conte
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23. Installation Guide 23.1.3.2 Ins
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23. Installation Guide BERN50 : $C
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23. Installation Guide If you have
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23. Installation Guide To make the
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23. Installation Guide List of Inst
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23. Installation Guide 23.2.4 Confi
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23. Installation Guide Configure me
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23. Installation Guide ${P}/EXAMPLE
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23. Installation Guide To recompile
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23. Installation Guide Page 574 AIU
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24. The Step from Version 4.2 to Ve
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BIBLIOGRAPHY Bock, H. (2004), Effic
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BIBLIOGRAPHY Janes, H. W., R. B. La
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BIBLIOGRAPHY Schaer, S. (1998), COD
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BIBLIOGRAPHY Page 588 AIUB
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INDEX OF PROGRAMS NEQ2ASC, 207, 541
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Index of Program Panels CODSPP 2: I
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Index of Program Panels MKCLUS 3: R
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INDEX OF KEYWORDS Antenna verificat
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INDEX OF KEYWORDS Cluster definitio
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INDEX OF KEYWORDS variance-covarian
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INDEX OF KEYWORDS orbit products, 1
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INDEX OF KEYWORDS Multi-session sol
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INDEX OF KEYWORDS Orbital elements
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INDEX OF KEYWORDS Receiver antenna
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INDEX OF KEYWORDS orbit modeling, 9
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INDEX OF KEYWORDS WGS-84, 19, 88, 2
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