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Dear Colleagues,

Mass-market devices such as smartphones carry a multitude of sensors and technologies that can be used for navigation and positioning in addition to GNSS, which can also provide a seamless indoor/outdoor navigation experience. In this context, Sensors is preparing a Special Issue on navigation and positioning related to the hybridization of GNSS with alternative ranging systems such as Wi-Fi Round Trip Time, ultra-wideband (UWB), Bluetooth, and 5G, and alternative positioning techniques based on magnetic field fingerprinting and others. This Special Issue will pay particular attention to solutions and techniques for smartphones.

Dr. Miquel Garcia-Fernandez
Guest Editor

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Keywords

GNSS
Wi-Fi RTM
Wi-Fi FTM
UWB Bluetooth
AoA
5G
magnetic field positioning
indoor navigation

Published Papers (2 papers)

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Research

16 pages, 4380 KiB

Open AccessArticle

Multi-GNSS Precise Point Positioning with UWB Tightly Coupled Integration

by Zhenchuan Huang, Shuanggen Jin, Ke Su and Xu Tang

Sensors 2022, 22(6), 2232; https://0-doi-org.brum.beds.ac.uk/10.3390/s22062232 - 14 Mar 2022

Cited by 7 | Viewed by 2585

Abstract

Global Navigation Satellite Systems (GNSSs) can provide high-precision positioning services, which can be applied to fields including navigation and positioning, autonomous driving, unmanned aerial vehicles and so on. However, GNSS signals are easily disrupted in complex environments, which results in a positioning performance with a significantly inferior accuracy and lengthier convergence time, particularly for the single GNSS system. In this paper, multi-GNSS precise point positioning (PPP) with tightly integrating ultra-wide band (UWB) technology is presented to implement fast and precise navigation and positioning. The validity of the algorithm is evaluated by a set of GNSS and UWB data. The statistics indicate that multi-GNSS/UWB integration can significantly improve positioning performance in terms of the positioning accuracy and convergence time. The improvement of the positioning performance for the GNSS/UWB tightly coupled integration mainly concerns the north and east directions, and to a lesser extent, the vertical direction. Furthermore, the convergence performance of GNSS/UWB solution is analyzed by simulating GNSS signal interruption. The reliability and robustness of GNSS/UWB solution during GNSS signal interruption is verified. The results show that multi-GNSS/UWB solution can significantly improve the accuracy and convergence speed of PPP. Full article

(This article belongs to the Special Issue Indoor–Outdoor Seamless Navigation for Mass-Market Devices)

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25 pages, 7595 KiB

Open AccessArticle

Automated Calibration of RSS Fingerprinting Based Systems Using a Mobile Robot and Machine Learning

by Marcin Kolakowski

Sensors 2021, 21(18), 6270; https://0-doi-org.brum.beds.ac.uk/10.3390/s21186270 - 18 Sep 2021

Cited by 8 | Viewed by 2615

Abstract

This paper describes an automated method for the calibration of RSS-fingerprinting-based positioning systems. The method assumes using a robotic platform to gather fingerprints in the system environment and using them for training machine learning models. The obtained models are used for positioning purposes during the system operation. The presented calibration method covers all steps of the system calibration, from mapping the system environment using a GraphSLAM based algorithm to training models for radio map calibration. The study analyses four different models: fitting a log-distance path loss model, Gaussian Process Regression, Artificial Neural Network and Random Forest Regression. The proposed method was tested in a BLE-based indoor localisation system set up in a fully furnished apartment. The results have shown that the tested models allow for localisation with accuracy comparable to those reported in the literature. In the case of the Neural Network regression, the median error of robot positioning was 0.87 m. The median of trajectory error in a walking person localisation scenario was 0.4 m. Full article

(This article belongs to the Special Issue Indoor–Outdoor Seamless Navigation for Mass-Market Devices)

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