Is software to check data to find out if it meets Alta positional tolerance only available in least squares pacakges?
If I turn sets of angles to a point from one set-up do I have enough data to determine a postional tolreance?
thanks for your help
> Is software to check data to find out if it meets Alta positional tolerance only available in least squares pacakges?
Yes. Star*Net would be a very good choice as far as simplicity and power goes.
Do I have to have a network to adjust in starnet or can I input the measurement data and check it to see if it meet the tolerance. It seems to me, that one ought to be able figure this without an adjustment. I was trying to run the least squares in the Survnet, mainly to get an ALTA tolerance report and I finally did it, but that software is not relly happy doing that......
thanks for your help
StarNet requires redundant data, not a network, to produce a tolerance report.
Thanks Mark, So does this mean simply more than one measurement?
> Thanks Mark, So does this mean simply more than one measurement?
Actually, you don't need redundant measurements to do error propagation analysis in Star*Net as long as you have realistic estimates of the standard errors of the measurements and observations. You'd need redundant measurement would be if you need to verify your s.e. estimates.
Okay you must be having fun now.... dizzy from chasing tail...
Let me just cut to the quick and state that you should be LS adjusting your data and that StarNet is one of the best packages available for that. Furthermore, StarNet Pro will simultaneously adjust GPS vectors, terrestrial, and levelling data. I dare say that once you are familiar with StarNet you will abandon your GPS manufacturer's software (TGO, TBC, LGO, TOPsurv or whatever) for anything other than vector resolution.
You do not need a network to benefit from LS. A point measured twice from the same instrument point and backsight is a network of sorts. It will yield an adjustment and the accompanying statistical report. The adjusted coordinate for such a simple data set will not differ from a simple meaning of the results unless you applied different weightings to the measurements(ie/ more data), but you get the picture.