STAR*NET V6 - Circe

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Chapter 8 Analysis of Adjustment Output In a STAR*NET survey adjustment, the number of degrees of freedom is the difference between the number of observations and the number of unknowns, i.e. the redundancy in the survey. Observations consist of the usual field measurements that are not declared free, together with any coordinate values entered with partial fixity. The count of unknowns includes all connected coordinates that are not fixed, one internal orientation for each direction set, and the computed transformations applied to GPS vectors. An alternate view of the Chi Square test is that it compares the Total Error Factor obtained in the adjustment against its expected value of 1.0. The total error factor is a function of the sum of the squares of the standardized residuals and the number of degrees of freedom in the adjustment. When the sum of the squares of the standardized residuals is exactly in the middle of its random distribution and as the number of degrees of freedom increases, the total error factor approaches exactly 1.0. The assumption that the adjustment residuals are due solely to random influences is rejected when the total error factor is larger than 1.0 by some magnitude dependent on the number of degrees of freedom and the confidence level desired. Since STAR*NET uses a one-tail Chi Square test, it fails the test only if the total error factor is greater than 1.0, how much greater depends on the number of degrees of freedom. With four degrees of freedom, failure occurs at 1.54; with ten at 1.35; with 100 at 1.12; and with 1000 at 1.04. If the total error factor is less than 1.0, the residuals are smaller than what is expected relative to the applied standard errors. If the total error factor is much less than 1.0, you have probably under estimated the quality of your observations, i.e. set your standard errors too large. For example, if there are 100 degrees of freedom in your job and the total error factor is less than 0.87, the sum of the squares of the standardized residuals falls within the bottom 2.5 percent of its expected random distribution. If STAR*NET were applying a two-tail Chi Square test, these “good” results would be rejected as having a non-random cause which should be investigated. In summary, the Chi Square test, often called the “goodness-of-fit test,” statistically tests whether your residuals are due to normal random errors. If the adjustment fails the test, first check the standard error values (weighting) you have assigned to your observations. If you find no problems there, then next check for mistakes which can include blunders in your actual observations, fieldbook recording errors, or data preparation errors such as incorrectly entered measurements or misnamed stations in the input data file. The failure of the Chi Square test is an alarm that indicates some problem and you then need to identify the source of the problem. Locating the source of problems is discussed later in this chapter. 124
Chapter 8 Analysis of Adjustment Output 8.9 Adjusted Station Information (Optional) STAR*NET optionally includes the final adjusted coordinates in the listing file. Since these coordinates are usually written to your output coordinates file you may wish to eliminate this section from your listing file to make it shorter. Adjusted Station Information ============================ Adjusted Coordinates (FeetUS) Station N E Elev Description 522 5002.0000 5000.0000 1000.0000 Iron Bar 546 5531.5463 6023.3234 1023.1328 Hole in One 552 5433.9901 6117.9812 1432.3413 Final Adjusted Coordinates (3D Example) Similarly, when adjusting a grid job, the final adjusted geodetic positions and ellipsoid heights are optionally included in this section of the listing file. For details about output for grid jobs, see Chapter 10, “Adjustment in Grid Coordinate Systems.” Sometimes an adjustment will not converge within the maximum iterations you specified in the Project Options. When an adjustment does not converge, this means that the change in the sum of the squares of the standardized (weighted) residuals from one iteration to the next never becomes less than the “Convergence Limit” value also set in the Project Options. This means the coordinates are still changing, and have not yet been adjusted to their “best fit” positions. When an adjustment does not converge, the following listing precedes the listing of the adjusted coordinates shown above. This is a warning to you which should indicate that something is wrong, and that the resulting coordinates are likely inaccurate. Every station having a coordinate that changed more than 0.00005 the last iteration is listed to help you determine where the problem is if possible. Warning - Solution Did Not Converge in 10 Iterations Excessive Coordinate Changes in Last Iteration Tolerance = 0.000050 FeetUS Station dN dE dZ 522 0.0020 0.0087 0.0002 Iron Bar 546 0.0063 0.3734 1.1338 Hole in One 552 0.0001 0.0002 0.0043 When An Adjustment Does Not Converge 125
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STAR*NET V6 Least Squares Survey Ad
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TABLE OF CONTENTS Chapter 1 OVERVIE
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10.9 Entering a Geoid Height and Ve
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Chapter 1 Overview 4. Survey planni
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Chapter 2 Installation 2.3 Starting
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2.7 The Registry Chapter 2 Installa
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3.3 The Menu System Chapter 3 Using
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3.8 Checking the Error File Chapter
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Chapter 3 Using STAR*NET 3.12 Displ
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Chapter 4 Options 4.2 Changing Proj
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Option Group: Units Chapter 4 Optio
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General Options Chapter 4 Options T
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Chapter 4 Options Option Group: Dis
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Chapter 4 Options What standard err
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Chapter 4 Options The default metho
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Option Group: Adjusted Contents Cha
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Other Files Options Chapter 4 Optio
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Chapter 4 Options Creating a Ground
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Special Options Chapter 4 Options T
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4.5 Company Options Chapter 4 Optio
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Chapter 4 Options Note that any dat
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Chapter 4 Options When the Instrume
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Using the Input Data Files Dialog C
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Chapter 5 Preparing Input Data 5.5
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Station Names Chapter 5 Preparing I
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Chapter 5 Preparing Input Data Zeni
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Point Descriptors Chapter 5 Prepari
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Example 1: (2D Data) Chapter 5 Prep
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Chapter 5 Preparing Input Data The
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Chapter 5 Preparing Input Data SING
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The “V” Code: Vertical Observat
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Chapter 5 Preparing Input Data Samp
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Example 2: (2D Data) Chapter 5 Prep
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Chapter 5 Preparing Input Data The
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Chapter 5 Preparing Input Data TRAV
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Chapter 5 Preparing Input Data Exam
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The “TE” Code: Ending a Travers
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Page 106 and 107: How do I weight observations? Chapt
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Page 110 and 111: Chapter 6 Running Adjustments The S
Page 112 and 113: 6.5 Preanalysis Chapter 6 Running A
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Page 116 and 117: Chapter 7 Viewing and Printing Outp
Page 118 and 119: 7.4 Viewing the Error File Chapter
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Page 146 and 147: Chapter 9 Tools As discussed above,
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Page 152 and 153: Chapter 10 Adjustments in Grid Coor
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Page 170 and 171: Appendix A STAR*NET Tutorial Exampl
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Appendix A STAR*NET Tutorial Exampl
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Appendix A STAR*NET Tutorial Before
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Example 5: Resection Appendix A STA
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Example 7: Preanalysis Appendix A S
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Appendix B References 6. Mikhail, E
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Appendix C Additional Technical Inf
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Appendix C Additional Technical Inf
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Appendix D Error and Warning Messag
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Data Lines, General Content Data Ty
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Index Installation Installing, 3 Se
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STARPLUS SOFTWARE, INC.
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STAR*NET V6 - Circe

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