Thanks to the generosity of Emlid, I am now the proud owner of two of their Reach precision GPS units. At a list price of $570 for a pair, these fall more into the category of low-cost rather than the ultra-low cost receivers I have been working with, but they do allow me to do some comparisons between the two. Their units use the more capable (and more expensive) Ublox M8T receivers rather than my Ublox M8N receivers and also have higher quality (and more expensive) Tallysman 4721 antennas, rather than the cheap antennas that were included with my receivers.
To compare the two I collected a fairly challenging data set, with maximum distances from the base station of over two kilometers and maximum velocities of over 70 km/hr, with relatively unobstructed rovers, but partially obstructed base stations. I mounted one of my receivers and a Reach unit on top of my car and also one of each at the base location. Here is a Google earth plot of the ground track. The Google Earth plots are a really nice feature of RTKPLOT I have not used until now but have quickly become a fan of. I could not make this feature work with the 2.4.3 version of RTKPLOT so had to go back to the 2.4.2 version. I also found I had to specify the solution format (out-solformat) as “xyz” instead of the “enu” that I usually use to get the solution in a format Google can use. The track was over a mix of dirt and paved roads running through agricultural fields and next to residential areas.
Here is a plot of the base station location, marked in red below. It is somewhat obstructed by the sheds and boats around it. I selected this location in part because it was very windy that day and this spot was fairly sheltered from the wind, but also thought it would make the solution a bit more challenging and therefore help differentiate the two receiver sets.
Most of the rover’s route was relatively unobstructed, but there were a few scattered trees near the road in some locations. The plot below shows an example of one of these spots. Note also, that the ground track goes off the road a bit at the end of the loop. I suspect this is due to inaccuracies in the base station location (and maybe the Google maps) rather than the RTKLIB solution since I did not make any attempt to calibrate the base station against any known reference.
Here’s the base station observation data, the M8N is on the left, the Reach M8T data on the right. From a cycle slip perspective they are fairly similar but we see a few of the satellites (G15, R16, and R18) are noticeably better with the Reach. This is most likely because of the higher quality antenna.
M8N Reach M8T
Looking at the SNR vs elevation for both receivers, we see the Reach has noticeably higher signal strength especially in the lower elevation (10-20 degrees) region where it is most important. Again, this is to be expected with the higher quality antenna. For some reason, the M8T SNR numbers are rounded off to the nearest integer. I don’t know why that is, but that is what makes the plots look like they are formatted differently.
M8N Reach M8T
Looking next at the rover data, here are the observations for the two receivers.
M8N Reach M8T
The rovers were stationary until 00:34 and then moving till 00:57, then stationary again. While they were moving and at the end when they were stationary, the two look fairly similar from a cycle-slip perspective with maybe a slight advantage for the Reach. However, during the initial stationary period, there were several slips that occurred simultaneously on every satellite in the M8N data. I’ve circled one of them in blue above. I believe these must be caused by some sort of discontinuity in the receiver and have nothing to do with the satellite signals themselves. My best guess is that they were caused by temperature fluctuations in the chip. It was a very hot day, with an intense sun heating the dark car roof, combined with a strong wind that would create a cooling effect. Because the antenna that was connected to the M8N receiver has only a one inch lead, it was mounted on top of the car in the sun, while the M8T receiver, with a longer antenna lead, was mounted inside the car and not subject to the same temperature fluctuations. Also, notice that the simultaneous slips all occurred near the beginning of the data set, possibly while the receiver was still reaching some sort of thermal equilibrium. To try and avoid this in the future, I will either switch to another inexpensive antenna I have with a longer lead, or let the receiver sit longer before starting to collect data.
Unfortunately these slips occurred during the initial stationary period I use for the first acquire and prevented that acquire from occurring. Rather than give up on the data, though, I decided to try running a solution with the M8N rover and the M8T base. I don’t know if it was because of the better signal strength, or because I just got lucky, but I was able to get an initial acquire with that combination. So for this exercise, the rest of the data is all based on a comparison between the M8N rover and the Reach M8T rover, both referenced to the M8T base station. It turns out that having a single base station also makes the accuracy analysis a little easier as I will describe later. This is not exactly the comparison I wanted to make, but one I think is still worth doing.
So how did they do? Here’s the solutions using my demo4 code. The input configurations were identical with one exception. Since with the M8T receivers, RTKLIB can resolve the GLONASS integer ambiguities without assistance, while with the M8N receivers, it can not, I set the input parameter “gloarmode” to “on” for the M8Ts and to “fix-and-hold” for the M8Ns. This enables my extension to the fix-and-hold feature to adjust for the additional errors on the GLONASS and SBAS satellites.
M8N Reach M8T
The Reach solution (on the right) looks very clean with a very fast acquire and then 100% fixed values after that. The M8N solution (on the left) also acquired quickly but then ran into the simultaneous cycle-slips, causing problems until it re-acquired at 00:40. After that it stayed fixed for nearly 100% of the time with a short dropout around 00:49.
The next questions, of course, are: Do the solutions match? And are the fixes all accurate? To check this, I will use a similar technique I did earlier when I had only two receivers, both mounted on the rover. For that case, I solved for the distance between the two receivers which forms a circle equal to the distance between the receivers. In this case, I will solve for the distance between each rover and the base, then difference the two. This should also give us a circle with radius equal to the distance between the two rover receivers. Having only one base simplifies things by avoiding addition of a second term caused by the separation between the two base receivers. Here’s the result of that operation, plotted only for the fixed solution points since those are the ones we are counting on to be accurate. On the left is the position difference (x,y,z) and on the right is the ground track difference.
M8N Reach M8T
The separation between the two receivers on the car roof was 15 cm and we see here that most of the points fall on the circle of that radius. However, there are several deviations, up to half a meter in error. They are also easy to see as spikes in the z-axis on the left plot. These are unexpected and quite concerning since we really rely on the fix status to let us know which points are valid and accurate.
Zooming in on the observation data for the largest of these spikes at around 00:51 shows that both rover receivers saw cycle slips on satellites G02 and G13 at this time, presumably from passing a tree or other obstruction.
M8N Reach M8T
Zooming in on the position data for this point, shows discontinuities in the Reach data but not the M8N data which is surprising, I had expected the opposite. As the driver of the car, I am certain that I did not drive over any meter high cliffs during the test, so the Reach M8T data must be wrong.
M8N Reach M8T
Looking at other error samples shows the same thing. It is more easily seen as spikes in the accelerations as shown here, especially the z-axis accelerations which only occur on the M8T data and not the M8N data
M8N Reach M8T
So what could be causing these errors? The two solutions used identical code and input parameters except for the fix-and-hold for GLONASS integer ambiguities setting. I reran the M8T solution with this parameter enabled to make them completely identical but this did not fix the problem. With the code being identical we have to suspect the difference is in the receivers themselves or at least in their setup. The next step I took was to use the Ublox u-center evaluation software to examine all the registers for both receivers. It’s a little trickier to do this with the Reach receiver since we don’t have direct access to the M8T chip, but there are instructions on setting up a tcp port in the Reach documentation, which is what I did.
For the most part, the differences between the two receiver setups were slight but I did find one significant difference. The receiver dynamic platform model settings are quite different. I have my M8N receivers set up for a “Pedestrian” model, while the Reach M8T receivers are set up for the “Airborne <4g” setting. According to the Ublox M8 Receiver Description document, that setting is only recommended for extremely dynamic environments. Here’s the details from the manual.
I have heard differing opinions on whether this setting affects the front-end of the receiver or whether it only affects the back-end position calculations. If it only affected the back-end, then this setting would not matter since we use only the raw GPS measurements from the receiver. However, if it does affect the front-end, we might expect it to have an effect like this since it would most likely be opening up the bandwidths of the phase lock loops tracking the carrier-phases and thus minimizing any filtering effects.
So that’s where things stand at the moment with this data set. I see issues with both receiver sets and have speculated on what may be causing the problems but have not had time to verify that either one of my guesses is correct. I had hoped to do that before posting this article but it’s been almost two weeks since my last post, so I’ve decided to just go ahead and post what I have.
This also gives me the chance to ask if anybody else has seen similar issues and/or might have other possible explanations for what is going on?
I have also uploaded this data to my data set library.