References

Etherington, C.; Naseer, R.; Conway, S.P.; Whitaker, Paul; Denton, M.; Peckham, Daniel

doi:10.1002/9781118694114.refs

Cited by 1 publication

(2 citation statements)

References 88 publications

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“…The Kalman Filter (KF) [ 63 ] is one of the most common implementations of Bayesian filters [ 1 ]. Kalman filtering is an algorithm which uses a series of measurements observed over time, including statistical noise and other inaccuracies, to produce estimates of unknown variables that are more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe [ 41 ].…”

Section: 3d Localization Techniquesmentioning

confidence: 99%

“…The late-nineteenth-century discovery of radio waves paved the way for radio-based navigation/positioning. Radio frequency signals have a greater transmission range than visible light while the can be transmitted through clouds or fog or even propagate as ground waves over vast distances, depending on the frequency of transmission overcoming the range issue for ground-based and satellite-based navigation systems [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of 3D Indoor Localization Systems and Technologies

Sesyuk

Ioannou

Raspopoulos

2022

Sensors

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Indoor localization has recently and significantly attracted the interest of the research community mainly due to the fact that Global Navigation Satellite Systems (GNSSs) typically fail in indoor environments. In the last couple of decades, there have been several works reported in the literature that attempt to tackle the indoor localization problem. However, most of this work is focused solely on two-dimensional (2D) localization, while very few papers consider three dimensions (3D). There is also a noticeable lack of survey papers focusing on 3D indoor localization; hence, in this paper, we aim to carry out a survey and provide a detailed critical review of the current state of the art concerning 3D indoor localization including geometric approaches such as angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), fingerprinting approaches based on Received Signal Strength (RSS), Channel State Information (CSI), Magnetic Field (MF) and Fine Time Measurement (FTM), as well as fusion-based and hybrid-positioning techniques. We provide a variety of technologies, with a focus on wireless technologies that may be utilized for 3D indoor localization such as WiFi, Bluetooth, UWB, mmWave, visible light and sound-based technologies. We critically analyze the advantages and disadvantages of each approach/technology in 3D localization.

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Section: 3d Localization Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%