Design And Implementation Of Indoor Positioning Using UWB Positioning Algorithm For Indoor Navigation

Siddiqa, Asima; Sahoo, Satyanarayana; Saraswathi, K

doi:10.1109/gcat55367.2022.9971871

Cited by 4 publications

(1 citation statement)

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“…In recent years, numerous emerging technologies for indoor pedestrian localization [1] have surfaced. Regarding applicability and effectiveness, the most widely employed positioning technologies can be broadly categorized into two types: inertial navigation positioning technology [2] and wireless positioning technology [3] .…”

Section: Introductionmentioning

confidence: 99%

Indoor pedestrian fusion localization algorithm based on unscented Kalman filter for UWB/PDR

Zhan,

Gao,

Liu

et al. 2024

Fourth International Conference on Sensors and Information Technology (ICSI 2024)

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In complex indoor environments, achieving satisfactory pedestrian localization using a single positioning technique proves challenging. For instance, Ultra-Wideband (UWB) positioning encounters non-line-of-sight errors in intricate indoor settings, while Pedestrian Dead Reckoning (PDR) technology with inertial sensors is susceptible to cumulative drift errors over time. Consequently, this paper introduces the Unscented Kalman Filter (UKF) algorithm to integrate UWB technology with PDR technology. The improved PDR-derived pedestrian localization information is employed as the state vector for the UKF algorithm, and the positioning information obtained through enhanced UWB technology serves as the observation vector for the UKF algorithm. This combined approach effectively corrects pedestrian position information, ultimately yielding more accurate pedestrian locations. Research results indicate that the proposed algorithm achieves a root mean square error of 3.64 centimeters. In comparison to a standalone UWB algorithm, this method demonstrates superior positioning accuracy in complex environments.

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Section: Introductionmentioning

confidence: 99%