A Kalman Filter Based Indoor Tracking System via Joint Wi-Fi/PDR Localization

Zhang, Hao; Xia, Yusheng; Liu, Kai; Jin, Feiyu; Chen, Chao; Liao, Yong

doi:10.1109/smartworld.2018.00250

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…With the rapid development of mobile internet and the internet of things, location-based service (LBS) applications become pervasive and rely on the location information of people in indoor environments [1]. Presently, the WiFi fingerprint localization method [2,3] has been favored because of widespread wireless infrastructures and low costs. On account of many random factors, such as diffraction, reflection, and refraction, WiFi localization results suffer severe localization errors, but keep stable in the long term.…”

Section: Introductionmentioning

confidence: 99%

“…(1) We exploit a fuzzy logic controller to balance the accuracy and energy consumption in the fusion localization using WiFi and PDR (2) We propose to utilize WiFi localization trajectory to correct the drift error of the heading estimate (3) In order to obtain the ground truths of the trajectory of pedestrians, we obtain the real-time coordinates of pedestrians at each step by the product of the step length and the step count…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR

Yan-kan

Huang

et al. 2023

Wireless Communications and Mobile Computing

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Fusing WiFi fingerprint localization and pedestrian dead reckoning (PDR) on smartphones is attractive because of their obvious complementarity in localization accuracy and energy consumption. Although fusion localization algorithms tend to improve localization accuracy, extra hardware and software involved will result in extra computations, such that energy consumption is inevitably increased. Thus, in this study, we propose a novel fusion localization scheme based on fuzzy logic, which aims to achieve ideal localization accuracy by consuming as little energy as possible. Specifically, energy-efficient inertial measurement unit (IMU) sensors are routinely called to provide the displacement of a smartphone user in the manner of PDR, whereas a fuzzy inference system is employed to adaptively schedule energy-hungry WiFi scans to fulfill WiFi fingerprint localization according to a coarse metric for fusion localization errors and the remaining energy of the smartphone, so as to achieve a trade-off between localization accuracy and energy consumption. Moreover, in order to mitigate the effect of drift errors induced by PDR, straight trajectories of the user are further identified using a series of WiFi localization results to calibrate heading estimates of PDR. Extensive experimental results demonstrate that the proposed scheme achieves the same accuracy as the complementary filter, but consumes 38.02% energy than the complementary filter, confirming that the proposed scheme can effectively balance the localization accuracy and energy consumption.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR

Yan-kan

Huang

et al. 2023

Wireless Communications and Mobile Computing

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“…To fuse information coming from Wi-Fi and from one or several additional technique(s), Kalman filtering is the most popular approach [13]. Many improvements to the baseline Kalman Filter (KF) have been used, such as the extended (EKF) or unscented KF (UKF) to deal with the orientation nonlinearity, multi-stage, and adaptive or robust versions.…”

Section: Introductionmentioning

confidence: 99%

A Constrained Kalman Filter for Wi-Fi-Based Indoor Localization with Flexible Space Organization

Sircoulomb

Chafouk

2022

Sensors

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This paper presents a constrained Kalman filter for Wi-Fi-based indoor localization. The contribution of this work is to introduce constraints on the object speed and to provide a numerically optimized form for fast computation. The proposed approach is suitable to flexible space organization, as in warehouses, and when objects can be spun around, for example barcode readers in a hand. We experimented with the proposed technique using a robot and three devices, on five different journeys, in a 6000 m2 warehouse equipped with six Wi-Fi access points. The results highlight that the proposed approach provides a 19% improvement in localization accuracy.

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A WiFi Assisted Pedestrian Heading Estimation Method Using Gyroscope

Yan-kan

Huang

et al. 2020

2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)

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A Kalman Filter Based Indoor Tracking System via Joint Wi-Fi/PDR Localization

Cited by 5 publications

References 14 publications

A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR

A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR

A Constrained Kalman Filter for Wi-Fi-Based Indoor Localization with Flexible Space Organization

A WiFi Assisted Pedestrian Heading Estimation Method Using Gyroscope

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