Bang & Olufsen (B&O), a Danish luxury audio company, envisions future sound systems that respond intuitively to a listener’s position — creating seamless, spatially adaptive audio experiences across rooms. Achieving this requires precise, room-scale indoor localisation.

This project develops an Ultra-Wideband (UWB)–based middleware that bridges raw radio-frequency ranging data to a usable, high-resolution spatial grid. The middleware fuses data from multiple distributed anchors to determine a user’s live position. Our design follows a three-layer architecture:

1. Edge layer: Multiple NXP Type-2BP UWB modules collect Time-of-Flight and Angle-of-Arrival data from an iPhone acting as a UWB transmitter.
2. Communication layer: A distributed MQTT Pub-Sub framework allows each anchor to publish its data over Wi-Fi to a central broker, ensuring scalability and resilience across rooms.
3. Processing layer: A Pose Graph Optimisation (PGO) algorithm fuses all incoming measurements into a globally consistent position estimate. Outlier rejection and a sliding-window filter reduce noise and reject erroneous readings in real time.

Across our controlled test rig, the middleware consistently improved position accuracy by ~32% over the worst-anchor baseline,  while rejecting roughly 10% of noisy data before fusion. The system not only reduced mean error by 3-4x, but also improved reliability. This demonstrates that even imperfect UWB readings can, through sensor fusion, yield stable, high-fidelity location data suitable for  responsive multi-room sound experiences.