Indoor Localization with Particle Filter in Multiple Motion Patterns

Li, Qiao; Liao, Xuewen; Gao, Zhenzhen

doi:10.1109/wcnc45663.2020.9120637

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…Due to the complementarity of these methods, WiFi localization and PDR are often integrated to achieve higher localization accuracy [13][14][15]. However, the fusion method causes high energy consumption.…”

Section: Related Workmentioning

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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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: Related Workmentioning

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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show abstract

“…Therefore, these errors accumulate over time and, in conclusion, lead to making PDR no more useful for positioning with long-term usage, as mentioned in [57]. The accumulative drift error caused by the low accuracy of IMU sensor is still a challenge of PDR and cannot be eliminated by itself [58]. Khedr and El-Sheimy [59] mentioned that PDR systems that suffer from the inherited errors are reliable for a limited period, and in order to correct and compensate those errors, an aid by other technologies is required.…”

Section: Dead Reckoning Technologymentioning

confidence: 99%

A Hybrid Indoor Positioning Model for Critical Situations Based on Localization Technologies

Mahdi

Chalechale

AbdelRaouf

2022

Mobile Information Systems

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The domains of positioning and tracking have undergone substantial evolution and advancements recently, especially within the concept of the Internet of Things (IoT) and in health care. Unfortunately, neither the current satellite positioning systems nor the standalone cellular systems remain useful for successfully localizing and tracking inside buildings. This paper proposes a new model that could improve the accuracy of localization in indoor environments. In addition, a broad review is conducted to discover the state-of-the-art indoor localization technologies appropriate for disasters and rescue situations. After a comprehensive study, three important technologies that need to be deeply reviewed are identified, which are wireless local area network (WLAN), dead reckoning (DR), and hybrid approaches. Based on these, a novel architecture is introduced that is more convenient to meet the operation of rescuing injured or older people in critical situations, where other technologies might be unavailable or require some extra infrastructures. The proposed model has two modes and selects one of these modes automatically. The first mode assumes the existence of both WLAN signals and smartphone sensors to be used for identifying the position of the object; otherwise, only smartphone sensors will be employed to achieve positioning. Significantly, the designated components and the flow control depicted provide a proper and suitable horizon for the next researchers who desire to develop a new indoor positioning system in this discipline with a low positioning root-mean-squared error on the centimeter scale that can later be incorporated in numerous applications relating to the IoT, health care, and evacuation plans.

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CRCLoc: A Crowdsourcing-Based Radio Map Construction Method for WiFi Fingerprinting Localization

Liao

Liu

et al. 2022

IEEE Internet Things J.

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Indoor Localization with Particle Filter in Multiple Motion Patterns

Cited by 5 publications

References 19 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 Hybrid Indoor Positioning Model for Critical Situations Based on Localization Technologies

CRCLoc: A Crowdsourcing-Based Radio Map Construction Method for WiFi Fingerprinting Localization

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