Bernese GPS Software Version 5.0 - Bernese GNSS Software

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9. Combination of Solutions files are combined to one set of parameters. If we want to stack the parameters pi and pi+1 into one parameter pi, we can use following parameter transformation: ⎛ ⎛ ⎞ 1 · · · ⎜ . ⎜ ⎟ ⎜ . ⎜ ⎟ ⎜ . .. ⎜ pi ⎟ ⎜ ⎜ ⎟ ⎜ 0 · · · ⎜ pi+1 ⎟ = ⎜ ⎜ ⎟ ⎜ 0 · · · ⎜ pi+2 ⎟ ⎜ ⎝ ⎠ ⎜ . ⎝ . .. . 0 · · · . . .. 1 · · · 1 · · · . . .. ⎞ 0 ⎟ . ⎟ 0 ⎟ 0 ⎟ . ⎠ ⎛ ⎞ ⎜ . ⎟ ⎜ ⎟ ⎜ pi ⎟ ⎜ ⎟ . ⎜ pi+2 ⎟ ⎝ ⎠ . (9.28) 0 · · · 0 · · · C 1 The transformation of the normal equation system is performed using Eqn. (9.22). Sometimes, parameters are stacked immediately after reading the normal equation system. But usually some type of parameter transformation precedes the stacking. Stacking is performed automatically for same parameters from different normal equation files, e.g., coordinates of the same station, troposphere parameters referring to the same station and the same epoch, or dynamic orbit parameters for the same satellite and the same osculating epoch. Stacking may be suppressed for station coordinates (e.g., in case of anomalous behavior) by marking the station as bad in the station information file (see Section 9.4.6). The coordinates for the marked station will then not be stacked but pre-eliminated before stacking for normal equation files within the time interval specified without any constraining. Orbital elements may be stacked after transformation to the same osculating epoch according to [Beutler et al., 1996]. For details see Section 15.3.2. 9.3.7 Reduction of the Number of Parameters Stacking reduces the number of unknown parameters in the normal equations. An important application is the reduction of the number of parameters used to represent a piece-wise linear function, see example in Figure 9.2. The operation is performed in two steps: first, the validity interval of each parameter is adjusted to the new interval according to Section 9.3.5. Then transformed parameters are stacked according to Section 9.3.6. A typical example is the reduction of number of troposphere parameters. If you have, e.g., estimated (and stored into normal equation files) 12 troposphere parameters per site and day, you have the possibility to reduce the number of parameters to 1, 2, 3, 4, or 6 values per day and site. See Section 9.4.5 for details on how to use this option. 9.3.8 Introducing Additional Parameters The introduction of additional parameters is possible in some specific cases, even if these parameter types have not been set up in the individual normal equations. Site motion parameters, or site velocities, are an example for such parameter types. It is necessary that the influence of these parameters can be neglected within the individual normal equations. Page 190 AIUB
x Figure 9.2: Reducing the number of parameters. 9.3 Manipulation of Normal Equations For the site velocities, e.g., the influence of the site motion may actually be neglected for the time span of one day. How to estimate velocities is shown in Chapter 10. Adding new parameters to the system of normal equations leads to a so-called expansion of the normal equation system. The procedure may be described by the parameter transformation (9.20) where p is the original, ˜p the expanded vector of parameters and C is given by ⎛ 1 · · · ⎜ C = ⎝ . . .. 0 0 · · · . . ⎞ 0 ⎟ . ⎠ = I 0 . (9.29) 0 · · · 1 0 · · · 0 Obviously, after performing the transformation of the normal equation system according to Eqn. (9.22), the resulting normal equation matrix Ñ becomes singular: N 0 b ˜p = . (9.30) 0 0 0 The singularity is removed by accumulating additional normal equations to the system. ADDNEQ2 applies this operation in five cases: (1) Estimation of station velocities (see below and Chapter 10). (2) Addition of stochastic pulses in long-arc combination (see Chapter 15). (3) Setup of geocenter coordinates (see Chapter 15). (4) Change of parameter representation for SINEX (see below). (5) Estimation of Helmert parameters between individual solutions (see Section 10.3.3). 9.3.8.1 Estimation of Station Velocities Coordinates of static stations are very stable in time in a terrestrial reference frame. The program GPSEST processes data stemming from time intervals not exceeding a few days (typically only one day). It is therefore reasonable and sufficient to model each station coordinate by a single value, only. However, the analysis based on the combination of normal equations may cover time intervals of several months or even years. It is necessary to take Bernese GPS Software Version 5.0 Page 191 t
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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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5. Preparation of Earth Orientation
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6. Data Preprocessing Preprocessing
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6. Data Preprocessing (a) AS turned
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6. Data Preprocessing 6.2.4 Code Sm
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6. Data Preprocessing is set to 2.
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6. Data Preprocessing 6.3.2 Preproc
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6. Data Preprocessing RMS of kin. s
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6. Data Preprocessing The ambiguiti
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6. Data Preprocessing no loss of si
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6. Data Preprocessing This epoch-di
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6. Data Preprocessing result in lar
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6. Data Preprocessing (e.g., from C
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6. Data Preprocessing The second pa
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6. Data Preprocessing GAR small pie
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6. Data Preprocessing -------------
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6. Data Preprocessing automated pro
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6. Data Preprocessing 6.6.2 Generat
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6. Data Preprocessing 6.6.3 Detect
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6. Data Preprocessing (6) If the to
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6. Data Preprocessing Page 138 AIUB
Page 168 and 169: 7. Parameter Estimation p u × 1 ve
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Page 196 and 197: 8. Initial Phase Ambiguities and Am
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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 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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14. Clock Estimation Page 308 AIUB
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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 20.4.1.4 Co
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20. Processing Examples 20.4.1.5 Ta
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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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