How to build a UWB Indoor Positioning System using ESP32 and Qorvo DWM3000

Custom PCB Board

Breadboard, 550 Tie Points

USB-A to Micro-USB Cable

Arduino IDE

Portenta UWB Shield

WROOMBEE -  ESP32 WROOM Xbee form factor

5V Power Source 

<html><body><h3><strong>Project Summary</strong></h3><p>Build a high-precision indoor positioning system capable of tracking objects with 10cm accuracy using Ultra-Wideband (UWB) technology. This project combines ESP32 microcontrollers with Qorvo DWM3000 UWB modules to create a real-time location tracking system that visualises movement on a floor plan with centimetre-level precision. </p><p> </p><figure><img src="https://projects.arduinocontent.cc/2c38c5c6-2d33-4ac8-90ae-a198ac442453.png"/><figcaption>UWB Indoor Positioning System using ESP32</figcaption></figure><h3><strong>Why This Project?</strong></h3><p>GPS fails indoors due to signal blockage by concrete, steel, and glass. This UWB-based solution overcomes those limitations by using radio pulse timing measurements between devices, making it ideal for: </p><ol><li>Warehouse asset tracking </li><li>Factory automation </li><li>Indoor robotics navigation </li><li>AR/VR applications </li><li>Airport navigation systems </li><li>Museum or exhibition tracking </li></ol><h3><strong>How It Works</strong></h3><p>The system uses Double-Sided Two-Way Ranging (DS-TWR) between one mobile tag and three fixed anchors: </p><ol><li>Tag - A Mobile device that moves around the space </li><li>Anchors - Three fixed reference points at known coordinates </li><li>Trilateration - Calculates tag position using distances from all three anchors </li><li>Real-time Visualisation - Python script displays movement on a floor plan </li></ol><p> </p><figure><img src="https://projects.arduinocontent.cc/1d154c70-54c8-4743-a134-ccfb5a517cfc.gif"/><figcaption>DWM3000 UWB positioning module</figcaption></figure><p> </p><h3><strong>Technical Approach</strong></h3><ol><li>Hardware: Each device pairs an ESP32-WROOM with a Qorvo DWM3000 UWB module via SPI </li><li>Ranging Protocol: DS-TWR measures Time-of-Flight (ToF) with nanosecond precision </li><li>Data Transmission: Tag sends distance measurements to PC via WiFi as JSON </li><li>Position Calculation: Python uses least-squares trilateration to determine coordinates </li><li>Accuracy: 10cm precision achieved through antenna delay calibration and median filtering </li></ol><h3><strong>Key Features</strong></h3><p>✓ Centimetre-level accuracy (10cm) for indoor positioning </p><p>✓ Real-time tracking with live floor plan visualisation </p><p>✓ WiFi connectivity for wireless data streaming </p><p>✓ Scalable architecture - easily add more anchors </p><p>✓ Multipath resistance - works in cluttered environments </p><p>✓ Signal quality monitoring - live RSSI display for each anchor </p><p>✓ Movement history - tracks and displays tag trajectory </p><h3><strong>Components Required</strong></h3><p><strong>Hardware </strong></p><ol><li>4× ESP32-WROOM Development Boards </li><li>4× Qorvo DWM3000 UWB Modules </li><li>Jumper wires for SPI connections </li><li>USB cables for programming and power </li><li>Computer for visualisation </li></ol><p><strong>Software </strong></p><ol><li>Arduino IDE with ESP32 board support </li><li>Python 3.x </li><li>Python libraries: matplotlib, numpy, scipy </li></ol><p> </p><figure><img src="https://projects.arduinocontent.cc/9c97882a-bbb6-4ebf-b1ec-f0ed72b2e4b3.jpg"/><figcaption>Position Tracker using Qorvo DWM300</figcaption></figure><h3><strong>Technical Specifications</strong></h3><p>Communication Protocol: IEEE 802.15.4z compliant </p><p>Frequency: Channel 5 (6.5 GHz) or Channel 9 (8 GHz) </p><p>Data Rate: 6.8 Mbps </p><p>Preamble: 128 symbols </p><p>Ranging Method: Double-Sided Two-Way Ranging (DS-TWR) </p><p>Update Rate: ~10 Hz </p><p>Range: Up to 30 feet indoors </p><p>Power: 3.3V operation (critical - higher voltage damages module) </p><p> </p><figure><img src="https://projects.arduinocontent.cc/08546f95-252a-4d51-8c0e-4254e6c4b86c.png"/><figcaption>Circuit Daigram</figcaption></figure><h3>System Architecture</h3><ol><li>Anchor Setup: Three ESP32+DWM3000 pairs placed at fixed, known coordinates </li><li>Tag Operation: Mobile ESP32+DWM3000 initiates ranging with each anchor sequentially </li><li>Distance Calculation: DS-TWR protocol measures precise time-of-flight </li><li>Data Pipeline: Tag → WiFi → JSON → Python → Trilateration → Visualization </li><li>Display: Real-time position plotted on floor plan background </li></ol><p> </p><figure><img src="https://projects.arduinocontent.cc/edbaa782-d996-4ff6-8db2-1a8f84a87c53.png"/><figcaption>DWM3000 Module Pinouts</figcaption></figure><p> </p><h3><strong>Software Components</strong></h3><p><strong>Firmware (Arduino) </strong></p><ol><li>Tag Code: Initiates ranging, calculates distances, sends JSON over WiFi </li><li>Anchor Code: Responds to ranging requests, provides timing information </li><li>DWM3000 Driver: Custom class handling all UWB radio operations </li><li>Filtering: The Median filter removes noisy measurements </li></ol><h3><strong>Python Visualization</strong></h3><ol><li>TCP Server: Receives JSON data from tag </li><li>Trilateration: Calculates position using least-squares optimisation </li><li>Real-time Plot: Displays tag position, movement path, and RSSI values on the floor plan </li><li>Update Rate: 100ms refresh for smooth visualisation </li></ol><h3><strong>Calibration Requirements</strong></h3><ol><li>Antenna Delay: Set to 16350 ticks to compensate for RF signal path delay </li><li>Anchor Positions: Must match physical placement and Python configuration </li><li>Clock Offset: Automatically compensated in DS-TWR calculation </li></ol><h3><strong>Applications</strong></h3><p><strong>Industrial: </strong></p><ol><li>Warehouse inventory tracking </li><li>Manufacturing floor asset management </li><li>Worker safety monitoring </li></ol><p><strong>Commercial: </strong></p><ol><li>Shopping mall navigation </li><li>Museum exhibit tracking </li><li>Airport baggage tracking </li></ol><p><strong>Robotics: </strong></p><ol><li>Autonomous mobile robot navigation </li><li>Drone indoor positioning </li><li>Multi-robot coordination </li></ol><p><strong>Research &amp; Development: </strong></p><ol><li>VR/AR spatial tracking </li><li>Motion capture systems </li><li>Human-robot interaction studies </li></ol><p><strong>Future Enhancements </strong></p><p>🔹 Add 4th anchor for improved stability and redundancy </p><p>🔹 Implement Time Difference of Arrival (TDoA) for multi-tag tracking </p><p>🔹 Develop a web-based dashboard for remote monitoring </p><p>🔹 Add 3D positioning with anchors at varying heights </p><p>🔹 Integrate with ROS for robotics applications </p><p>🔹 Implement NLOS detection using RSSI/first-path analysis </p><h3><strong>Project Outcome</strong></h3><p>A fully functional indoor positioning system capable of: </p><ol><li>Tracking a mobile tag with 10cm accuracy </li><li>Visualising position in real-time on a floor plan </li><li>Monitoring signal quality from each anchor </li><li>Recording and displaying movement history </li><li>Operating reliably in cluttered indoor environments </li></ol><p>Perfect for makers, researchers, and engineers interested in precision indoor localisation, UWB technology, and practical IoT applications! </p><p>This project, <a href="https://circuitdigest.com/microcontrollers-projects/diy-indoor-uwb-positioning-system-using-esp32-and-qorvo-dwm3000">UWB Indoor Positioning System using ESP32 </a>, demonstrates the power where GPS fails. With proper calibration and setup, you can achieve positioning accuracy that rivals expensive commercial systems using affordable development boards and modules. </p><p></p><p> </p></body></html>

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How to build a UWB Indoor Positioning System using ESP32 and Qorvo DWM3000

GPS stops at the door. This project starts where GPS fails.