UMAC status

The UMAC status is used by the ABD RC software to verify if the RT is accurate enough for it to be safe for it to preform certain tests. Tests like path following need RTK but ones like push tests can be done in differential or WAAS. 

The different levels on position accuracy (bad, poor, weak, OK, good) check the horizontal position accuracy against various levels, outlined in the table below.
 
How we, at OxTS, define our internal position accuracy (used in NCOM) and how we define the accuracy used in the UMAC status is slightly different.

The OxTS form that you see in the NCOM data in NAVdisplay are standard deviations, \(NorthAcc\) and \(EastAcc\). These are calculated from the square roots of the Kalman Filter state variances for latitude and longitude before being converted in metres in Northing and Easting.

The ABD form used in the UMAC status is computed as:

$$ { \sqrt{NorthRs^2 + EastRs^2}}$$

\(NorthRs^2\) and \(EastRs^2\) are the “total square errors” of the position state variables of the whole navigation system, again as metres in Northing and Easting. $$ {NorthRs^2 = NorthErr^2 + NorthAcc^2}$$and $${EastRs^2 = EastErr^2 + EastAcc^2}$$ \(NorthErr\) and \(EastErr\) represent the KF filters current understanding of the North and East error (our Kalman Filter tracks position errors not absolute values) that has not yet been used to correct the output.  Combining the two provides are more responsive "worst-case" measure of the North and East error. The final output is $${\sqrt{NorthErr^2 + EastErr^2 + NorthAcc^2 + EastAcc^2}}$$

So in summary:

OxTS: \(NorthAcc\) and \(EastAcc\)

ABD: $$ { \sqrt{NorthErr^2 + EastErr^2 +NorthAcc^2 + EastAcc^2 }}$$
The fewer terms and the division by two in the OxTS form are going to make the numbers for OxTS NCOM smaller than in the UMAC state.

For reference, the various UMAC statuses are listed below: