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Advances in Computer and Communication

ISSN Online: 2767-2875 CODEN: ACCDC3
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ArticleOpen Access http://dx.doi.org/10.26855/acc.2026.03.004

UWB/IMU Fusion Localization in Coal Mine Faces Using Improved Particle Filter

Junyan Qi1, Yuxue Sun2,*, Lei Wang2, Zhuli Ren3

1School of Software, Henan Polytechnic University, Jiaozuo 454000, Henan, China.

2School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, Henan, China.

3School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, Henan, China.

*Corresponding author: Yuxue Sun

Published: March 2,2026

Abstract

Positioning systems in underground coal mines are challenged by severe multi-path propagation and electromagnetic interference, resulting in non-line-of-sight (NLOS) ranging errors and inertial drift. This study proposes a breakthrough cooperative Ultra-Wideband (UWB)-Inertial Measurement Unit (IMU) positioning framework integrating an enhanced Particle Filter (PF) architecture, aimed at delivering a high-precision and robust solution for personnel positioning in high-risk underground coal mining areas. First, a hybrid error compensation model integrating Taylor Series Expansion (TSE) and Sage-Husa Unscented Kalman Filter (SH-UKF) is constructed. The TSE method linearizes NLOS errors in UWB ranging values through polynomial approximation, while SH-UKF dynamically estimates residual error coefficients to achieve nonlinear correction of compensation quantities. Subsequently, a Hunter-Prey Optimization-based Adaptive Weighted Particle Filter (HPO-AWPF) is proposed. This algorithm enhances the global search capability of HPO by introducing adaptive weight factors and designing a Mahalanobis Distance-based adaptive weight allocation strategy to optimize the probability density matching of UWB/IMU observation data. The experimental results demonstrate that the proposed algorithm can alleviate the influence of nonlinear observation on the distribution of particles, effectively solve the problem of particle degradation, and has better robustness and positioning accuracy compared with existing algorithms.

Keywords

Ultra-Wideband; Inertial Navigation; Hunter Prey Optimization; Adaptive Particle Filter; Multi-Sensor Fusion Localization

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How to cite this paper

UWB/IMU Fusion Localization in Coal Mine Faces Using Improved Particle Filter

How to cite this paper: Junyan Qi, Yuxue Sun, Lei Wang, Zhuli Ren. (2026) UWB/IMU Fusion Localization in Coal Mine Faces Using Improved Particle Filter. Advances in Computer and Communication, 7(1), 22-37.

DOI: http://dx.doi.org/10.26855/acc.2026.03.004

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