RTKLIB on a drone with u-blox M8T receivers

Drones are a popular application for RTKLIB and quite a few readers have shared their drone-collected data sets with me, usually with questions on how they can get better solutions. In many cases, the quality of this data has been fairly poor and it has been difficult to get satisfactory results. I was curious to understand why this environment tends to be so challenging since in theory a drone should have more open skies than just about any other application.

To do an experiment, I bought an inexpensive consumer drone from Amazon. I chose the X8C from Syma since it is beginner model and a little larger than some options. I figured the larger size should make it better able to carry some extra weight.

After a few practice flights to get the hang of flying it, I used some duct tape and double-sided foam adhesive to attach a u-blox antenna and 90 mm diameter ground plane to the top of the drone and a u-blox M8T receiver with my custom CHIP data logger underneath where the camera usually goes. I used the landing gear as a spool to wind the unnecessary five meters of antenna cable which was the heaviest part of the whole setup. From a weight perspective, the Emlid Reach units would have been a better choice, but I wanted to collect data from the Galileo constellation of satellites as well as GPS and GLONASS so I used my CSG receiver with the newer 3.0 firmware. I used a second CSG receiver mounted on top of my car as the base station.  Here’s a stock photo of the drone on the left and after my modifications on the right.


Although the drone was able to lift the extra weight fairly easily, it seemed to affect the stability of the flight control system and after a few minutes the prop motors would start to fight each other. At that point the drone would start to descend even at full throttle and the drone would land hard enough to usually bounce on its side or back. Still I was able to make a number of short flights which were adequate for testing purposes.

Here’s the observation data for the first set of flights, base station on the left and drone on the right. Red ticks are cycle-slips and gray ticks are half-cycle ambiguities. Ideally, the drone data would look as clean as the base but as you can see it is significantly worse and it turned out to be unusable for any sort of reliable position solution.  The regions without cycle-slips in the drone observations are the times in between flights in which the drone is sitting on the ground.


Clearly, while the drone is flying, something is interfering with the GPS receiver or antenna, most likely either EMI or mechanical vibration. I could have used a fancy test stand and RF sniffer to try and locate the source of interference but since this blog is focused on low-cost solutions I just used some duct tape, a steel bar, and the RTKLIB code instead.

I used two types of duct tape, both the polyester/fabric type that everyone calls duct tape, and also the metal foil type that is actually used to repair or install ducts. I first used the non-metal duct tape to securely attach the landing gear to the heavy steel bar. The steel bar was convenient because it was easy to attach but anything heavy enough to prevent the drone lifting off under full throttle would work fine.

I then started an instance of RTKNAVI on my laptop and connected it to the receiver on the drone.  The goal was to simulate a complete drone flight while the drone was sitting on the ground and at the same time watch the RTKNAVI observations to detect any degradation of the measurements.  I used a wireless connection but a USB cable would have worked too.

Unfortunately RTKNAVI won’t plot the observation data real-time, but by selecting the tiny “RTK Monitor” box in the bottom left corner of the main RTKNAVI screen, then choosing “Obs Data” from the menu, I was able to get a continuously updating listing of the observations.  Cycle-slips show up as non-zero values in the first column with the I heading. I chose a location outdoors with open enough skies that any degradation in the observation data would be obvious.


I first observed the cycle-slip column with the drone powered down to verify I wasn’t getting any cycle-slips on all but the lowest elevation satellites. I then continued to observe the cycle-slip column while sequencing through the steps required to fly the drone. I first powered on the drone, then powered on the transmitter, then issued the calibration/connection sequence, then turned on the throttle to low. So far, so good, no sign of cycle-slips. I then started moving the joysticks to issue steering commands which caused the motors to change speeds. All of a sudden I started getting cycle-slips, the more aggressive the steering commands, the more cycle-slips I saw. Aggressive changes in throttle also caused cycle-slips but full throttle with no adjustments or steering commands was fine.

Next I moved just the antenna, then just the receiver away from the drone while issuing steering commands. Moving the antenna away had no effect but moving the receiver away eliminated the cycle-slips.

At this point my guess was that the interference was coming from the relatively high power switching in the motor control circuits and that the antenna ground plane was shielding the antenna from this interference but nothing was shielding the receiver. To test this theory, I attached a layer of the metal duct tape to the bottom of the drone to act as a shield between the drone controller board and the receiver.  I then re-attached the receiver to the bottom of the drone and re-ran the experiment. This time there were almost no cycle-slips even with the most aggressive steering.

I then removed the steel bar and ran a second set of short flights with the layer of metal tape still in place. I was a little concerned that the new shield would interfere with commands sent from the transmitter to the drone so I first tested everything while still on the ground and then kept the drone fairly close during the flight. Fortunately I didn’t see any sign of commands not getting through.

The drone data looked much cleaner in this flight!  Unfortunately, this time the base data was no good with many simultaneous cycle-slips throughout the observation data. At this point I realized that I had placed the base station receiver directly on the top of the car when collecting the data which was very hot at the time. Usually I keep the receiver in the car to avoid this and only place the antenna on the roof. I have seen this kind of severe temperature effects cause simultaneous cycle-slips before but never to this extent. Again the data was completely unusable.

So, back out there again for a third round of flights. This time, everything looked much better. I still saw a few cycle-slips, especially when first applying the throttle at take-off, so my shielding was not perfect but a dramatic improvement over the first flight. The plots below show the results. The top two plots are position solutions for the z-axis. The top plot is with continuous ambiguity resolution and the middle plot is with fix-and-hold enabled. The bottom plot is the drone observation data.


I made three adjustments to the input configuration file from what I would normally use for my car based measurements.  First of all, since the drones have very open skies, I adjusted the minimum elevation angles from 15 degrees to 10 degrees.   Then, after plotting and observing the accelerations from an initial solution, I increased the vertical acceleration dynamics estimate (stats-prnaccelv) from 0.25 to 1.0.  Finally, because I was seeing slightly higher position variances in the initial solution than I usually do, I adjusted the position variance AR threshold (pos2-arthres1) from 0.004 to 0.1  Both of these last two changes would make sense if the level of vibration were higher in the drone than I am used to seeing, which is quite likely.

Each time the drone landed/crashed due to the unstable flight control system it would bounce to the side or upside-down and that is what is causing the cycle-slips and switch from fix to float at the end of each flight. As you can see though in every case I quickly get another fix after I put the drone upright again. The fixes are solid enough to hold through the entire flight even in continuous mode for all but one of the flights. With fix-and-hold enabled all flights maintained 100% fix rate. The data is as good as or better than similar experiments where I have mounted the rover on top of a car.

This is not surprising since the skies are more open in this experiment. Having over twenty satellites available for ambiguity resolution also helped. I used all the satellites (GPS/GLONASS/Galileo/SBAS) for ambiguity resolution and took advantage of the new feature in the demo5 b26 code that cycles through all the satellites and will throw a single one out if it is preventing a fix. This will automatically occur anytime the number of satellites available for ambiguity resolution is greater than the config parameter “pos2-mindropsats” which defaults to twenty.

I have added the raw data and the configuration file to the  sample data set section at rtkexplorer.com

I imagine different drones will have different issues and not all will be as easy to fix as this one, but the method described here or something similar should be helpful any time drone data is not looking as clean as the base station data.

The fix I chose was very easy to implement but a better fix would probably have been to wrap just the receiver in a shield rather than placing a shield between the control board and the receiver. This would protect the receiver better and avoid affecting commands sent from the transmitter.  In fact, based on these results, I suspect shielding the GPS receiver on a drone is always a good idea.


7 thoughts on “RTKLIB on a drone with u-blox M8T receivers”

  1. Really love your work! I’ve been following for a bit now…
    Would be great if raw data could be taken from on-board UAV GPS and PPK’d…
    Thank you for really great site. I will continue to learn much from you!


  2. Nice informative post as usual. I did a lot of drone work from the mid 90s through the first decade of this century and EMI would always be an issue to some extent when doing kinematic positioning with a drone. In general the larger the craft the easier it was to obtain good results. Manned craft were real easy. Separation distance is the simplest fix if you have room.

    I ran similar tests primarily looking at the receiver generated signal to noise ratio for each satellite. Using a large electric helicopter (800 mm blades) as an example you would see the signal to noise ratio drop as the flight power demands increased. Blade spin-up on the ground had a minimal effect. Lift off and sustained climbs would drop things enough to typically cause cycle slips. Level off in a hover and a fix could be regained. Drop straight down through the prop wash (higher vibrations, but low power consumption) and the GPS signal was good. Nothing really surprising here. EMI is going to be the likely issue on smaller craft, especially rotory wing.

    What can be done about it? Separation distance if you have it. If you don’t shielding the receiver and/or other EMI emitting components can help. Basically what you have done is the first good step.

    Of course every setup is a little different so there can be all kinds of potential issues. The nice thing about GNSS receivers is almost all of them allow detailed diagnostic output to help track down receiving issues.


    1. Hi Cynfab. No, if Galileo is enabled it will be used for AR. It’s actually the same for GPS in the release code. It’s only in the demo5 code that I added an switch for GPS so that I could experiment with GLONASS only AR.


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