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hpalmer
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 accuracy of gnss sensors are generally expressed as a fixed amount plus 1 or 0.5 ppm (rms).  I recall these are the same values from 20 years ago.  

Why are static and rtk accuracy for sensors different? 

Where did the 1 ppm come from in RTK? and why different than 0.5ppm for static?

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Plumb Bill
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Posted by: hpalmer

 accuracy of gnss sensors are generally expressed as a fixed amount plus 1 or 0.5 ppm (rms).  I recall these are the same values from 20 years ago.  

Why are static and rtk accuracy for sensors different? 

Where did the 1 ppm come from in RTK? and why different than 0.5ppm for static?

The drift in accuracy stated in PPM (as distance between base/rover) exist because there may be different atmospheric conditions at each location.  This, in turn, results in a different propagation of the signal waves through the atmosphere.  Static sees a lesser impact, because a good static processing engine (TBC for example) can analyze and control for different variables and outlier observations in a much more robust way than just RTK.  It can shape the solution using a statistical analysis.  An RTK accuracy estimate on a data collector is usually only a simple averaging of a lot of little data sets - which can include some that aren't as good as others.  I have definitely seen PPM play an impact when there was different weather at a VRS site than where I am surveying - usually the vertical will drift out first.  Then it's time to set up a local base (which works the best usually because the major variable cancel out - seeing as both base/rover are effectively at the same location).

PPP is a horse of a different color - and these days engines like OPUS and Trimble's RTX are rather impressive with the accuracy and precision they can accomplish.  Through quite a bit of testing I've found RTX to be more precise than OPUS - but not more accurate (in any way I could evaluate with standard surveying equipment).

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Bill93
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Those numbers must apply to observations of some lengths that need to be specified, and undoubtedly very different ones.

 

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MightyMoe
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Lots of testing, I will have to say that the accuracy statements for the R-10 are valid from my experience.

RTK will be slightly less accurate simply because there is less data to process. 

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Plumb Bill
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Agreed.  The RMS values on the data collector can be a different story sometimes, but usually only if it starts creeping over a tenth. Sub-tenth they're pretty reliable.

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Paul in PA
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Static involves a lot of repetitive observations. Start with an understanding of statistics before trying to understand GNSS.

Paul in PA

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hpalmer
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was the 60's and statistics was dull but logic was fun.

I still want to know where the 1/1 million came from and why most manufacturers produce the same relative accuracy for their sensors.

I don't think they are talking about observations as lots of other factors are involved (antenna, environmental) including other stuff way over my head. 

 

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Plumb Bill
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While attending a seminar on Trimble VRS I heard one of the Trimble engineers that works on their GNSS describe that the performance can be better or worse than 1ppm depending on the relative atmospheric conditions at the base or rover.  This would lead me to believe that these numbers are a statement of expected accuracy based on a lot of testing.  For example, I'd expect sometimes you'd see better than 1ppm in Arizona, and worse in the Pacific NW depending on weather conditions.

This is also why they tout the virtual solution as better in the VRS scheme, but I usually see just fine performance connecting to a single mountpoint and can store the vectors that way.

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Dave Karoly
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I think it has to do with initialization.

The Static processor initializes every observation independently.

The Kinematic processor does one initialization for a series of observations. The initialization is valid as long as lock on the satellites is maintained.

edit: fixing iOS stupid edits.

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Jim Frame
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An RTK accuracy estimate on a data collector is usually only a simple averaging of a lot of little data sets

I'm told that Javad averages the weighted value of each epoch.  I wouldn't be surprised if that's true for others as well.

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