Two-Layer Ultra-Wideband Localization: Scalability for Dense Wearable Motion Capture

Abstract

Abstract

A recurrent challenge in scaling ultra-wideband (UWB) motion-capture systems is interference management whenmanyranging transactions coexist in time and space. To address this, we study a two-layer localization architecture that separates field-level player localization from local on-body pose tracking, allowing the two tasks to operate with different communication regimes and spatial-reuse policies. A stochastic-geometry framework is used to map sport-dependent parameters, including player density, field size, tag count, anchor count, update rates, and ranging airtime, to reliability and update-rate tradeoffs. The analytical model is parametrized based on controlled experiments that characterize ranging success under temporal overlap, player distance, and variable-delay scheduling, which we use to design a proximity-aware local coordination strategy. We apply our proposed approach to soccer, volleyball, and ice hockey as representative use cases. Our results show that proximity-aware coordination can provide a scalable and lightweight interference management mechanism. Coordination is activated only where local player clustering creates strong interference, while spatially separated players continue to share resources without coordination. For the highest density scenario tested, this increases the local-layer ranging success from below 50% without coordination to over 80% in fourand eight-player congestion clusters, while avoiding network-wide coordination overhead.