HYFI: Hybrid Floor Identification Based on Wireless Fingerprinting and Barometric Pressure

Zhao, Fang; Luo, Haiyong; Zhao, Xuqiang; Pang, Zhibo; Park, Hyuncheol

doi:10.1109/tii.2015.2491264

Cited by 57 publications

(42 citation statements)

References 20 publications

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“…References [1], [19], [20] all proposed a 3D indoor positioning method based on PDR using a low-cost IMU sensor system equipped with a 2D information fusion barometer to achieve the 3D trajectory tracking of pedestrians. Zhao et al [21] proposed an algorithm for complex floor recognition based on wireless fingerprint and air pressure as a solution for elevation positioning. This method is a floor recognition technology that obtains floor information from wireless AP distribution to initialize and calibrate air pressure.…”

Section: Related Workmentioning

confidence: 99%

Indoor Multi-Floor 3D Target Tracking Based on the Multi-Sensor Fusion

2020

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In recent years, indoor target tracking based on pedestrian dead reckoning (PDR) and the builtin inertial sensors of smartphone has become a research hotspot in location-based services (LBS). However, indoor 3D target tracking using smartphone inertial measurement unit (IMU) mainly face challenges of error accumulation caused by the heading drift of sensors and height fluctuation caused by the instability of barometer. This paper proposes a multi-floor 3D target tracking system based on the built-in inertial sensors of smartphone. We first establish a 2D PDR movement model by raw sensor data and then 2D PDR position is corrected in real time by rebuilding the particle filter model and refining the calculation method of particle weight to reduce the accumulated errors. A height displacement measurement method based on Kalman filter and floor change detection (FCD) algorithm is proposed to extend the 2D PDR tracking to 3D space. We first skillfully use Kalman filter to fuse the data of barometer and accelerometer, after that, the FCD algorithm is proposed to evaluate and modify the output height of the Kalman filter, evaluating the floor change state and maintaining steady height. The 3D target tracking, which consists of real-time 2D trajectory information and height information, is provided to the pedestrian. Experimental results demonstrate that the proposed method based on the fusion of various technologies can effectively maintain track stability and smoothness with low cost and high positioning accuracy. Moreover, additional peripheral devices need not be arranged in advance. INDEX TERMS 3D target tracking, pedestrian dead reckoning (PDR), particle filter, Kalman filter, multisensor fusion.

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Section: Related Workmentioning

confidence: 99%

Indoor Multi-Floor 3D Target Tracking Based on the Multi-Sensor Fusion

2020

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“…In this paper, we use a barometric pressure information-based floor identification algorithm [47] that identifies floors with more than 96.1% accuracy.…”

Section: Positioning Modelmentioning

confidence: 99%

An Infrastructure-Free Indoor Localization Algorithm for Smartphones

Wang

Luo

Men

et al. 2018

Sensors

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Accurate indoor positioning technology provides location-based service for a variety of applications. However, most existing indoor localization approaches (e.g., Wi-Fi and Bluetooth-based methods) rely heavily on positioning infrastructure, which prevents their large-scale deployment and limits the range at which they are applicable. Here, we proposed an infrastructure-free indoor positioning and tracking approach, termed LiMag, which used ubiquitous magnetic field and ambient lights (e.g., fluorescent, incandescent, and light-emitting diodes (LEDs)) without containing modulated information. We conducted an in-depth study on both the advantages and the challenges in leveraging magnetic field and ambient light intensity for indoor localization. Based on the insights from this study, we established a hybrid observation model that took full advantage of both the magnetic field and ambient light signals. To address the low discernibility of the hybrid observation model, LiMag first generated a single-step fingerprint model by vectorizing consecutive hybrid observations within each step. In order to accurately track users, a lightweight single-step tracking algorithm based on the single-step fingerprints and the particle filter framework was designed. LiMag leveraged the walking information of users and several single-step fingerprints to generate long trajectory fingerprints that exhibited much higher location differentiation ability than the single-step fingerprint. To accelerate particle convergence and eliminate the accumulative error of single-step tracking algorithm, a long trajectory calibration scheme based on long trajectory fingerprints was also introduced. An undirected weighted graph model was constructed to decrease the computational overhead resulting from this long trajectory matching. In addition to typical indoor scenarios including offices, shopping malls and parking lots, we also conducted experiments in more challenging scenarios, including large open-plan areas as well as environments characterized by strong sunlight. Our proposed algorithm achieved a 75th percentile localization accuracy of 1.8 m and 2.2 m, respectively, in the office and shopping mall tested. In conclusion, our LiMag algorithm provided location-based service of infrastructure-free with significantly improved localization accuracy and coverage, as well as satisfactory robustness inside complex indoor environments.

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“…central processing unit. Moreover, the antenna tile may set up a floor-integrated WiFi access point for communication with wearable devices [19] and/or fixed wireless infrastructure, or for indoor positioning via WiFi fingerprinting [20].…”

Section: Introductionmentioning

confidence: 99%

Biodegradable Dual Semicircular Patch Antenna Tile for Smart Floors

Khalili

Caytan

Deckmyn

et al. 2019

Antennas Wirel. Propag. Lett.

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A dual semi-circular microstrip patch antenna implemented on a biodegradable substrate is presented for operation in the [863-873]-MHz and [2.4-2.5]-GHz frequency bands. To cover these frequency bands, two semi-circular patches are compactly integrated onto a biodegradable cork tile, commonly found as support in laminate flooring, serving as a substrate. Thereby, the antenna tile may be seamlessly embedded as a sublayer of the floor structure. A higher-order mode is generated by applying via pins in the antenna topology, to produce a conical radiation pattern with a null at broadside and sectoral coverage in the vertical plane. As such, the concealed-floor antenna covers all azimuth angles of arrival in smart houses. The antenna performance is fully validated, also when the tile is covered by different PVC sheets. Owing to the supplementary design margins, the antenna impedance bandwidth remains covered. Moreover, the radiation patterns are measured in various elevation planes. In stand-alone conditions, a radiation efficiency and a maximum gain of 74.3 % and 5.8 dBi at 2.45 GHz and 48.1 % and 2 dBi at 868 MHz are obtained. Its omni-directional coverage in the horizontal plane, stable performance on the inhomogeneous and biocompatible cork substrate and for various inhomogeneous superstrates and its low-profile integration make the proposed antenna an excellent candidate for smart floors and smart houses.

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HYFI: Hybrid Floor Identification Based on Wireless Fingerprinting and Barometric Pressure

Cited by 57 publications

References 20 publications

Indoor Multi-Floor 3D Target Tracking Based on the Multi-Sensor Fusion

Indoor Multi-Floor 3D Target Tracking Based on the Multi-Sensor Fusion

An Infrastructure-Free Indoor Localization Algorithm for Smartphones

Biodegradable Dual Semicircular Patch Antenna Tile for Smart Floors

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