Accurate Position and Orientation Estimation for UWB-Only Systems Using a Single Dual-Antenna Module

This paper proposes a complete cascade pipeline for accurate position and orientation estimation using a single dual-antenna UWB module. First, an extended Kalman filter (EKF) fuses distance measurements from multiple anchors to estimate the agent’s position. The estimated position is then used to derive orientation. To overcome the critical challenge of front–back ambiguity in orientation estimation, we introduce a novel method that integrates a multi-hypothesis testing (MHT) framework with a circular likelihood metric (CLM). This method enumerates all feasible angle of arrival (AoA) hypotheses via MHT and assesses their consistency using the CLM, thereby selecting the most probable hypothesis to resolve ambiguity. Comparative simulations demonstrate that this “position-first, orientation-later” cascade enhances robustness over joint optimization by preventing the propagation of AoA noise to the position estimates. Extensive evaluations, including high-precision rotary table experiment and real-world field trials, validate the system’s efficacy in providing precise location and heading information. This work delivers a complete, low-cost, and robust solution for autonomous navigation in challenging environments.

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Publication Details

Journal
Electronics
Published
2026-01-14
DOI
https://doi.org/10.3390/electronics15020369
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Accurate Position and Orientation Estimation for UWB-Only Systems Using a Single Dual-Antenna Module

Peng Han, Che Zhang, Yan Li
Electronics
Indoor and Outdoor Localization Technologies
article

Accurate Position and Orientation Estimation for UWB-Only Systems Using a Single Dual-Antenna Module

Peng Han, Che Zhang, Yan Li
article en

Abstract

This paper proposes a complete cascade pipeline for accurate position and orientation estimation using a single dual-antenna UWB module. First, an extended Kalman filter (EKF) fuses distance measurements from multiple anchors to estimate the agent’s position. The estimated position is then used to derive orientation. To overcome the critical challenge of front–back ambiguity in orientation estimation, we introduce a novel method that integrates a multi-hypothesis testing (MHT) framework with a circular likelihood metric (CLM). This method enumerates all feasible angle of arrival (AoA) hypotheses via MHT and assesses their consistency using the CLM, thereby selecting the most probable hypothesis to resolve ambiguity. Comparative simulations demonstrate that this “position-first, orientation-later” cascade enhances robustness over joint optimization by preventing the propagation of AoA noise to the position estimates. Extensive evaluations, including high-precision rotary table experiment and real-world field trials, validate the system’s efficacy in providing precise location and heading information. This work delivers a complete, low-cost, and robust solution for autonomous navigation in challenging environments.

ElectronicsVol. 15(2)
Northeastern University (CN)
Openalex Percentile: Top 88%
Indoor and Outdoor Localization Technologies
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