Deterministic Wireless Propagation Model Assisted Indoor Positioning

Wilson, Conor; Lang, Hans-Dieter; Li, Yunbo; Sarris, Costas D.; Zhang, Xingqi

doi:10.1109/aps/ursi47566.2021.9704349

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…In Equation (7), N is the number of selected frequency points; Δf is the corresponding frequency interval; U (ω n , x, y, z) is the field distribution u at different frequency points, and ω n denotes the frequency; t m is the propagation time:…”

Section: Physics-based Radio Wave Propagation Modelmentioning

confidence: 99%

“…To solve this problem, many techniques have been studied for vehicle localisation in tunnels. The fingerprinting algorithm is a commonly used technique for localisation [6][7][8][9] because it has low complexity and takes a short online process time. This algorithm can be divided into two main phases: a fingerprint database is built in the offline phase, and the position is predicted in the online phase.…”

Section: Introductionmentioning

confidence: 99%

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Physics‐based wave propagation model assisted vehicle localisation in tunnels

Qin

Zhang

2023

IET Microwaves Antenna & Prop

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Connected and autonomous vehicles systems can provide a safe and convenient transportation solution through wireless communication between vehicles and roadside communication infrastructure. The vehicle's ability to establish its location plays an important role in such systems. This article presents an efficient localisation framework by combining physics‐based wireless propagation models and fingerprint localisation algorithms. To that end, a parabolic wave equation (PWE)‐based wireless channel simulator is utilised to obtain the direction of arrival (DOA) values that construct the fingerprint dataset. A detailed procedure on how to obtain the DOA information using PWE, as well as analysis and guidelines on the selection of the key parameters of the localisation framework are provided. Numerical results are compared with theoretical data in terms of accuracy, and the selection of parameters during the localisation process is investigated in actual road tunnel cases. Besides, various numbers of wireless access points and schemes of fingerprinting algorithms have been studied, showing the capability of the proposed approach to be employed for the pre‐design of wireless communication systems.

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Section: Physics-based Radio Wave Propagation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Qin

Zhang

2023

IET Microwaves Antenna & Prop

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“…The fingerprinting process consists of two steps [6], the offline phase and the online phase. It is necessary to measure the received signal strength (RSS) from all wireless access points (APs) at different reference points (RPs) during the offline stage.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the online phase, the positioning algorithm compares the RSS vector received by users at an unknown location with the offline fingerprint database to estimate the location of users. In addition, experiments show that by increasing the number of RPs or the amount of fingerprint data collected by each RP in the fingerprint database, the localization accuracy of fingerprinting can be effectively improved [6]. Even though fingerprint-based technology is extensively used and straightforward, its commercial feasibility has always been limited since the physical measurement of a dense fingerprint database at the offline stage necessitates a significant investment in labour, which is also one of the most severe challenges faced by fingerprint-based localization in the long term.…”

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confidence: 99%

Received signal strength reconstruction using pix2pix generative adversarial network

Wu,

Qin,

Zhang

2023

Electronics Letters

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Positioning technology based on received signal strength (RSS) fingerprints has emerged as a vital research topic in indoor localization due to its high accuracy and low cost. Increasing the density of offline fingerprints collected can effectively improve localization accuracy in the online stage, but it will result in astronomical collection costs. RSS reconstruction using generative models is an efficient solution to dramatically reduce fingerprint collection costs while maintaining excellent accuracy. In this paper, the authors propose a pix2pix generative adversarial network based RSS reconstruction model, which can generate a dense RSS fingerprint map based on only the location information of the wireless access point. The accuracy and efficiency of the proposed model are verified in an indoor environment.

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Received Signal Strength Prediction Using Generative Adversarial Networks for Indoor Localization

Wu,

Qin,

et al. 2023

2023 Photonics &Amp; Electromagnetics Research Symposium (PIERS)

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Deterministic Wireless Propagation Model Assisted Indoor Positioning

Cited by 4 publications

References 5 publications

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Received signal strength reconstruction using pix2pix generative adversarial network

Received Signal Strength Prediction Using Generative Adversarial Networks for Indoor Localization

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