Towards mm-Level Accurate UWB Radar: High-Accuracy Phase-Based Obstacle Detection through Multi-Channel Fusion

2026-06-15

AI Summary

Achieving centimeter-level ranging in passive ultra-wideband (UWB) radar systems is highly challenging due to the absence of labels, weak reflections, and multipath interference. This work proposes a signal processing framework that jointly exploits amplitude and phase information across multiple frequency channels. It pioneers the effective use of phase data in passive UWB systems by employing a line-of-sight reference to correct hardware-induced phase drift and resolves phase ambiguity through multi-channel fusion, thereby mitigating Fresnel-zone-specific attenuation at individual frequencies. Experimental validation using a DW3000-based bistatic setup in a realistic metallic industrial environment demonstrates a median ranging error of 1.69 cm—representing an order-of-magnitude improvement over amplitude-only methods. Furthermore, multi-channel integration reduces the error by over 40% compared to single-channel approaches, approaching sub-centimeter accuracy.

Abstract

Accurate, tag-free distance estimation with ultrawideband (UWB) radar is essential for applications such as autonomous guided vehicles, robotics, and environment characterization. For tag-based localization systems, phase-based UWB signal processing techniques have demonstrated sub-wavelength ranging precision, but these approaches are not applicable for passive (tagless) radar setups with weak reflections, mixed multipath conditions, and the absence of a known time-of-flight (ToF) first-path reference. This paper demonstrates for the first time that phase information can be effectively exploited in a fully passive UWB radar setting. We introduce a signal processing framework that extracts reliable distance information by combining coarse amplitude-based estimates with high-resolution phase changes across multiple frequency channels. By referencing phase measurements with the line-of-sight component, the method compensates for hardware-induced phase drift, while the use of multichannel frequency diversity enables disambiguation of periodic phase information and improves robustness against frequencyspecific channel degradation such as Fresnel zones. The proposed approach is validated on a robot equipped with a bistatic UWB radar using DW3000 devices and evaluated in a realistic metallic industrial environment. Experimental results show that our work consistently achieves centimeter-level accuracy even at high speeds, with a median error of 1.69 cm, significantly outperforming existing ~10cm accuracy UWB radar approaches relying only on amplitude-information. We further show how multi-channel fusion exploits uncorrelated channel degradation to reduce the error by more than 40% compared to single-channel operation, and outline how phase modeling and fusion can be pushed toward sub-centimeter accuracy.

Problem

• UWB radar
• passive sensing
• phase-based ranging
• obstacle detection
• distance estimation

Innovation

• phase-based ranging
• multi-channel fusion
• passive UWB radar
• centimeter-level accuracy
• frequency diversity