Multi-System Fusion Positioning Method Based on Factor Graph

IF 3.2 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Signal Processing Letters Pub Date : 2024-10-15 DOI:10.1109/LSP.2024.3480833

Hongmei Wang;Sheng Xing;Zhiwei Wang;Minghui Min;Shiyin Li

引用次数: 0

Abstract

Ultra-wideband (UWB) positioning system offers high-precision location capabilities. However, it introduces positive biases in complex environments. Pedestrian Dead Reckoning (PDR) algorithm based on Inertial Measurement Unit (IMU) can maintain robust tracking even in cases of abrupt changes in pedestrian trajectories but suffers from cumulative errors. Therefore, in this study, the strengths of both systems are combined. Hence, a factor graph model is established to enhance the multi-system fusion localization method based on factor graphs. Experimental verification in both straight-line trajectories and scenarios involving state mutations demonstrates an integrated average positioning accuracy within 0.1m. When compared to traditional system fusion localization methods, the accuracy is enhanced by more than 50%.

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基于因子图的多系统融合定位方法

超宽带（UWB）定位系统具有高精度定位能力。然而，它在复杂环境中会产生正偏差。基于惯性测量单元（IMU）的行人惯性导航（PDR）算法即使在行人轨迹突然变化的情况下也能保持稳健的跟踪，但会出现累积误差。因此，在本研究中，两种系统的优势被结合起来。因此，建立了一个因子图模型，以增强基于因子图的多系统融合定位方法。在直线轨迹和涉及状态突变的场景中进行的实验验证表明，综合平均定位精度在 0.1 米以内。与传统的系统融合定位方法相比，精度提高了 50%以上。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Signal Processing Letters 工程技术-工程：电子与电气

CiteScore

7.40

自引率

12.80%

发文量

339

审稿时长

2.8 months

期刊介绍： The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.