Why does my dwm1001 always have an error of 20cm

Hi, everyone.

Recently,I use the DWM1001-examples(https://github.com/Decawave/dwm1001-examples/tree/master/examples) as the software for DWM1001 hardware

I test on the open lawn, whether it is 3m or 10m or 20m, there is always an error of 20cm. For example, I write two dwm1001 tags into the TWR program and place them on both ends of the 5m scale, and the Distance obtained is always between 520cm ± 5cm. Why is the error of 20cm? How do I adjust the program to get the value of 500cm ± 5cm?

So does anyone have an idea on this problem? I think I need some help. Thanks!

Best regards!

for dw1000 TWR, there is a distance/rssi related ranging bias, if you want to get higher ranging result, you should compensate this error in your ranging code using bias-vs-distance table.

you can find more info in section 3.2 of TWR ranging bias.

Hey there!

That was a previous question of mine too and i think i found the “solution” in my case.

I dont think the range bias compensation would help having the 20 cm (or 25 cm in my case). Low errors it may be a good way but 20 cm i dont think that.

In my case, i’m using MDEK1001 devices and i used the OTP values stored (crystal trim, antenna delay, smart tx,…) on the start up on all devices. But the Antenna Delay value i think it comes with an intencion to have a “positive error” (real_mesure - obtained_measure). So if you “sum” the bouth devices error that could be the some of the 20 cm of your error.

A good test is to have another tag with a different antenna delay and see if that error changes.

Try to compensate the antenna delay on the tag in a reference distance (5.010 meter) and then try to to move it in other distances and see if that reduces that error.

Note that this only is necessessary to reach some value of error because another variables gona make the error variable like the temperature that affects antenna delay. I read here that some of the devices goes of with 17 cm of error and 2 cm of standard deviation.

Another thing that i notice is that value to compensate works good on LOS situation but on NLOS could affect in a negative way.

Hope i could help.


thanks! I will try it
Thank you very much~

thanks a lot! It’s very helpful~
I offer with my sincere thanks :smiley: