Channel Sounding with nRF54L15 – Poor Accuracy Compared to Nordic's Demo

[Ibai]

Hi Nordic team,

I'm currently working on a real-time distance measurement project using channel sounding with the nRF54L15 DKs. I’ve been using the channel_sounding_ras_initiator and channel_sounding_ras_reflector samples from your official GitHub repository, and I’ve managed to get the system running successfully.

However, the performance I’m getting in terms of distance accuracy and responsiveness is noticeably worse than what’s shown in your YouTube demo (https://www.youtube.com/watch?v=dbQKqXN80ms). In your video, the distance tracking appears smooth and accurate, even when the devices are in motion.

In my case, the measurements are much more noisy, and there’s a significant delay (sometimes several seconds) between physical movement and updated distance readings. I’ve only made minor modifications to the sample code—such as increasing buffer sizes and applying a median filter to reduce noise.

My questions are:

1. Is the code used in the YouTube demo exactly the same as the channel_sounding_ras_initiator and channel_sounding_ras_reflector samples, or was it modified for the demo?

2. Are there specific hardware requirements or environmental conditions (e.g., antenna placement, orientation, shielding) that are crucial for achieving the best performance?

3. Is any calibration or parameter tuning needed beyond what is included in the sample projects?

I’d really appreciate any tips or insights on how to get results closer to what you demonstrate in the video.

Thanks in advance,

Ibai

[SwRa]

Hello,

Which version of the nRF Connect SDK are you using.? You need to use the version 3.0 and using the IFFT.. 

I’ve only made minor modifications to the sample code—such as increasing buffer sizes and applying a median filter to reduce noise.

You don't need to do this if you are using v3.0 of the SDK as it has the filter. Also, make sure you are using the nrf samples and not the ones in Zephyr: https://docs.nordicsemi.com/bundle/ncs-3.0.2/page/nrf/samples/bluetooth/channel_sounding_ras_initiator/README.html and https://docs.nordicsemi.com/bundle/ncs-3.0.2/page/nrf/samples/bluetooth/channel_sounding_ras_reflector/README.html 

Best Regards,

Swathy

[Ibai]

Hi Swathy,

Thanks for your response.

I can confirm that I’m using nRF Connect SDK version 3.0.2, and I’m working with the official Nordic samples (not the Zephyr ones), specifically:

• channel_sounding_ras_initiator

• channel_sounding_ras_reflector

When both boards are stationary and facing each other, the distance estimations are quite accurate and stable. However, when either board is in motion, the measurements become significantly more noisy and fluctuate a lot. This makes real-time tracking unreliable in dynamic scenarios.

Do you have any recommendations on improving performance while moving? For example, would increasing the measurement rate or using specific antenna orientations help?

Thanks for your support.

[PaKa]

Please define "significantly more noisy and flucutate a lot". This to be able to determine if this is inside expecations or not.

[Ibai]

Hi again,

Thanks for your follow-up.

To clarify what I mean by "significantly more noisy and fluctuating":

When both boards are placed facing each other and the reflector moves linearly and steadily toward the initiator, the IFFT-based distance estimations are not behaving as expected. Specifically:

• The measured distance sometimes increases, even though the reflector is clearly moving closer to the initiator.

• Additionally, the measurements show high variability, with noticeable fluctuations even when the movement is smooth and at a constant speed.

This inconsistent behavior occurs despite maintaining proper alignment and a clear line of sight between the boards. When both boards are stationary, the estimations are much more stable and accurate.

Is this deviation expected in dynamic scenarios, or could it be related to how the IFFT processing handles movement?

Thanks again for your support.

[PaKa]

The distance estimation accuracy will be impacted by the change in environment so moving it will move it through different environments and distance estimation will this be impacted.

Without actual numbers it is impossible to comment if what you see is inside expectations or not.