Towards mm-Level Accurate UWB Radar: High-Accuracy Phase-Based Obstacle Detection through Multi-Channel Fusion
2026-06-15 • Robotics
Robotics
AI summaryⓘ
The authors show a new way to measure distances accurately using ultrawideband radar without relying on tags or beacons. They combine simple amplitude measurements with detailed phase information from multiple frequencies to get precise distance estimates, even in tough environments with reflections and noise. Their method corrects hardware errors and improves accuracy to about 1.7 cm, much better than previous methods that only used amplitude and had around 10 cm error. They tested this on a robot in an industrial setting and suggest their approach could get even more precise with further improvements.
ultrawideband (UWB) radarphase-based signal processingtime-of-flight (ToF)multipath propagationline-of-sightfrequency diversitybistatic radarFresnel zonesamplitude-based rangingphase drift compensation
Authors
Jelle De Moerloose, Adnan Shahid, Eli De Poorter
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.