A Novel 3-D Indoor Localization Algorithm Based on BLE and Multiple Sensors

Yu, Yue; Chen, Ruizhi; Chen, Liang; Zheng, Xingyu; Wu, Dewen; Li, Wei; Wu, Yuan

doi:10.1109/jiot.2021.3055794

Cited by 75 publications

(28 citation statements)

References 46 publications

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“…Similar approaches were investigated in [32]- [34]. Furthermore, Yu et al [35] combine BLE with a inertial navigation system (INS) and PDR, to also obtain accurate heading and speed estimations. Another common concept is combining BLE and UWB, what allows for several different approaches.…”

Section: Combined Localizationmentioning

confidence: 99%

Multimodal Indoor Localization: Fusion Possibilities of Ultrasonic and Bluetooth Low-Energy Data

et al. 2022

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The resilience of indoor localization systems is a main concern of their industrial application. A combination of different techniques can enhance the overall robustness of such systems. In this work, we present fusion possibilities of coarse Bluetooth Low Energy localization based on the received signal strength indicator and the finer ultrasound time difference of arrival (TDOA) technique.This approach offers the advantage to robustify the high-accuracy ultrasonic localization in areas with non-optimal coverage. Moreover, the data fusion enables to enhance the overall localization area in a cost effective manner. This contribution proposes and evaluates (i) novel methods of how the ultrasonic system can be extended to a constrained area and (ii) a novel possibility to incorporate available Bluetooth signal strength information in the TDOA algorithm to improve accuracy.

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Section: Combined Localizationmentioning

confidence: 99%

Multimodal Indoor Localization: Fusion Possibilities of Ultrasonic and Bluetooth Low-Energy Data

et al. 2022

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“…Yu et al 16 proposed a three-dimensional (3D) indoor localization algorithm combining low-power Bluetooth with multi-sensor. It combines Inertial Navigation System (INS) with Pedestrian Dead Reckoning (PDR) to accuracy lead and estimate speed.…”

Section: Related Workmentioning

confidence: 99%

A study on the cabin indoor localization algorithm based on adaptive K-values

Gao

Tao

Qin

et al. 2022

International Journal of Distributed Sensor Networks

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In ocean voyages, cabin indoor localization plays a considerably important role in ship safety management. Due to the special structure of ships and the influence of internal and external environment, the mainstream indoor positioning technology nowadays is not ideal for positioning inside the cabin. In order to improve the positioning accuracy, this article proposes an adaptive K-value-based cabin indoor positioning algorithm. The algorithm constructs a fingerprint library by collecting Received Signal Strength Indication data and carries out filtering; matches fingerprint information by adaptive K-values during the localization process, while using double K-nearest neighbor to reduce the influence of outlier points on the final localization; and finally uses the multi-point mass center method to determine the final localization results. The experimental results in the automated cabin laboratory show that the average positioning error of the algorithm is 1.74 m, which can well meet the cabin indoor positioning requirements.

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“…Thus, IMUs are commonly used alongside other technology that can provide absolute localization. IMUs have been widely used in indoor localization in multi-floor environments to provide real-time location estimates as the user moves [180], [181], [199]- [201].…”

Section: G Inertial Measurement Units (Imus)mentioning

confidence: 99%

“…Due to the natural existence of magnetic fields everywhere and the growing availability of magnetometers in the form of MEMS sensors incorporated in smartphones, magnetic field signals can be used for indoor localization. Magnetism has been used in conjunction with other technologies for indoor localization in multi-floor environments to improve the localization performance [128], [199], [201].…”

Section: H Magnetismmentioning

confidence: 99%

A Survey of Indoor Localization Systems in Multi-Floor Environments

Mostafa¹,

Harras²,

Youssef³

2022

Preprint

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This work presents a survey for the indoor localization systems handling multi-floor environments, including floor localization, and estimating the floor and the 2D location of the user. It focuses on approaches targetting users and user devices. The survey comprehensively covers various techniques and technologies focusing especially on the recent solutions to give insights to the researchers for further development in the domain of indoor localization. Finally, several challenges are addressed and possible solutions are proposed pointing to future research directions. No data was collected for this work.

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A Novel 3-D Indoor Localization Algorithm Based on BLE and Multiple Sensors

Cited by 75 publications

References 46 publications

Multimodal Indoor Localization: Fusion Possibilities of Ultrasonic and Bluetooth Low-Energy Data

Multimodal Indoor Localization: Fusion Possibilities of Ultrasonic and Bluetooth Low-Energy Data

A study on the cabin indoor localization algorithm based on adaptive K-values

A Survey of Indoor Localization Systems in Multi-Floor Environments

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