STAR*NET V6 - Circe

Chapter 6 Running Adjustments
You can also run Preanalysis using an existing data set that contains field data. All
observations will be ignored. This can be useful if you wish to simulate the addition of
new field measurements to an existing survey, perhaps to improve positional accuracies
in one part of the network. With STAR*NET’s Preanalysis option, you simply add
distance or angle lines (without field data) to an existing data file, run the preanalysis,
and look at the predicted error ellipses. Note however that approximate coordinates must
be supplied for all points in the network even though observations already exist on the
lines of data.
After Preanalysis has completed, you can view the Listing File to see the predicted
standard deviations and error ellipses for the proposed survey stations. Note that there
are no residuals listed, because no actual field data measurements were entered or
processed. You can also choose to view the plot and look at the predicted error ellipses
superimposed on the network. The actual dimensions and orientations of the ellipses can
help you to decide whether your proposed survey will meet the required specifications
for individual point accuracies.
If the predicted ellipses are too large, you may need to add more observations, improve
the accuracy of your observations (by reducing their standard errors), or possibly both.
On the other hand, if your ellipses are extremely small, you may be able to reduce the
amount of field data you are planning to acquire.
To use Preanalysis correctly, you must make several assumptions:
1. That you can indeed survey the approximate configuration proposed in the data file.
Once you get into the field, obstructions may force you to change your plans. The
use of topographic maps and aerial photographs to plan the survey design can help
reduce this problem.
2. That you can observe distances and angles to the accuracy you specified in the
project options. Preanalysis will not help you if you simulate the network to much
greater accuracy than you can actually measure it.
3. That your field measurements will not contain blunders.
Even with these constraints, preanalysis is a powerful tool to help you test various
network configurations before any field work is done, and to test the effects of adding
new measurements to an existing survey.
107