Challenger RP2040 UWB (DWM3000) – Arduino toolchain Examples

This project shows how to program the Challenger RP2040 UWB module with the Arduino toolchain to

1. get a raw UWB data dump
2. compute simple distance values

• Read the main project PDF here: rp2040_uwb_progress.pdf
• First raw data example code: raw_data_dump.ino

ToDo / Project Tasks

This project is part of a student project at HTW Berlin, supervised by
Prof. Dr.-Ing. Steffen Borchers-Tigasson
https://www.htw-berlin.de/hochschule/personen/person/?eid=12130

• 0. Installation / bring-up / establishing communication with the UWB chips

  • 0.a) BU03-DW3000 via Raspberry Pi Pico
  • 0.b) Challenger DWM3000
  • Set up interfaces, e.g. Thonny, Arduino IDE, Windows Serial Debug Assistant
  • Basic documentation and simple test program (e.g. LED blink)

• 1. Create calibration data locally on the Pico/Challenger (requires 1 anchor and 1 tag)

  • 1.a) Create a table:
    Distance (measured, real) | Distance (via UWB)
  • 1.b) For 1 m, 2 m, 4 m, 8 m, 16 m collect 1000 data points each and save as CSV
  • 1.c) Evaluate accuracy and precision (mean values, variances) on the PC; transfer the data from the Pico to the PC

• 2. Determine / measure maximum data rate (requires 1 anchor and 1 tag)

  • 2.a) Store distance data with timestamp (ms range) locally on the Pico, at least 1000 measurements
    Table: time | Distance (via UWB)
    Goal: determine measurement rate (frequency) and vary the data rate parameter (via AT commands on BU03, Challenger?)
    Validate the configured data rate and push it towards the maximum (target: 60–100 Hz)
  • 2.b) Evaluation (mean, variance, min, max)

• 3. Vary measurement method and repeat tasks 1 and 2

  • Both chips support different measurement methods (e.g. TDoA, bidirectional)
  • Compare methods regarding accuracy, precision and measurement rate

• 4. Set up a real-time data connection from Pico to host PC via USB serial

  • Send Pico data to the host in (near) real-time
  • Insert the data into a database (in-memory or SQLite)

• 5. Build a sensor network consisting of 4 anchors and 2 tags

  • 5.a) Setup / topology configuration
  • 5.b) Data transmission and functional testing

• 6. Perform 3D localization on the PC with real-time data

  • Goal: output and update x, y, z coordinates in real-time
  • Possible methods:
    • simple: Pythagoras / multilateration
    • medium: optimization-based methods
    • advanced: AI-based approaches

• 7. Improve position accuracy using a Kalman filter

• 8. Connect the system to the PTZ camera

  • Use position data for camera control
  • Test tracking and pointing accuracy