Cargando…

Non-GNSS Smartphone Pedestrian Navigation Using Barometric Elevation and Digital Map-Matching

Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problem often require external reference signals or specialized hardware, the extra size, weight, power,...

Descripción completa

Detalles Bibliográficos
Autores principales:	Broyles, Daniel, Kauffman, Kyle, Raquet, John, Smagowski, Piotr
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2018
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068906/ https://www.ncbi.nlm.nih.gov/pubmed/29997351 http://dx.doi.org/10.3390/s18072232

Ejemplares similares

A Hybrid Indoor Localization and Navigation System with Map Matching for Pedestrians Using Smartphones
por: Tian, Qinglin, et al.
Publicado: (2015)

Enhanced Vertical Navigation Using Barometric Measurements
por: Narayanan, Shrivathsan, et al.
Publicado: (2022)

GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation
por: Peltola, Pekka, et al.
Publicado: (2018)

Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation †
por: Di Pietra, Vincenzo, et al.
Publicado: (2020)

RTK with the Assistance of an IMU-Based Pedestrian Navigation Algorithm for Smartphones
por: Niu, Zun, et al.
Publicado: (2019)

Smartphone-Based Activity Recognition in a Pedestrian Navigation Context
por: Jackermeier, Robert, et al.
Publicado: (2021)

An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services
por: Bang, Yoonsik, et al.
Publicado: (2016)

Pressure-Pair-Based Floor Localization System Using Barometric Sensors on Smartphones
por: Yi, Chungheon, et al.
Publicado: (2019)

Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket
por: Deng, Zhi-An, et al.
Publicado: (2015)

Carrying Position Independent User Heading Estimation for Indoor Pedestrian Navigation with Smartphones
por: Deng, Zhi-An, et al.
Publicado: (2016)

Udiometrical, Thermometrical, and Barometrical Statements
por: Pole, T.
Publicado: (1810)

Udiometrical, Thermometrical, and Barometrical Statements
por: Pole, T.
Publicado: (1809)

Magnetic-Map-Matching-Aided Pedestrian Navigation Using Outlier Mitigation Based on Multiple Sensors and Roughness Weighting
por: Kim, Yong Hun, et al.
Publicado: (2019)

Barometrical Pressure as a Factor in Medicine
por: Burwood, T. Wesley
Publicado: (1898)

Indoor Positioning Based on Pedestrian Dead Reckoning and Magnetic Field Matching for Smartphones
por: Kuang, Jian, et al.
Publicado: (2018)

LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
por: Tang, Jian, et al.
Publicado: (2015)

Pedestrian Augmented Reality Navigator
por: Mahapatra, Tanmaya, et al.
Publicado: (2023)

Map-Based Indoor Pedestrian Navigation Using an Auxiliary Particle Filter
por: Yu, Chunyang, et al.
Publicado: (2017)

Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
por: Liu, Yang, et al.
Publicado: (2018)

GNSS Spoofing Detection Based on Coupled Visual/Inertial/GNSS Navigation System
por: Gu, Nianzu, et al.
Publicado: (2021)

Accurate Collaborative Globally-Referenced Digital Mapping with Standard GNSS
por: Narula, Lakshay, et al.
Publicado: (2018)

Monocular Camera/IMU/GNSS Integration for Ground Vehicle Navigation in Challenging GNSS Environments
por: Chu, Tianxing, et al.
Publicado: (2012)

INS/CNS/GNSS integrated navigation technology
por: Quan, Wei, et al.
Publicado: (2015)

Special Issue on GNSS Data Processing and Navigation
por: Rovira-Garcia, Adria, et al.
Publicado: (2020)

Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning
por: He, Zhe, et al.
Publicado: (2013)

Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors
por: Liu, Qiang, et al.
Publicado: (2023)

A Stochastic Approach to Noise Modeling for Barometric Altimeters
por: Sabatini, Angelo Maria, et al.
Publicado: (2013)

Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ)-Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation
por: Renaudin, Valérie, et al.
Publicado: (2014)

A Training Smartphone Application for the Simulation of Outdoor Blind Pedestrian Navigation: Usability, UX Evaluation, Sentiment Analysis
por: Theodorou, Paraskevi, et al.
Publicado: (2022)

A Navigation Probability Map in Pedestrian Dynamic Environment Based on Influencer Recognition Model
por: Qiao, Zhi, et al.
Publicado: (2020)

Inertial Indoor Pedestrian Navigation Based on Cascade Filtering Integrated INS/Map Information
por: Fan, Menghao, et al.
Publicado: (2022)

Smartphone GNSS Performance in an Urban Scenario with RAIM Application
por: Angrisano, Antonio, et al.
Publicado: (2022)

Optimizing the Use of RTKLIB for Smartphone-Based GNSS Measurements
por: Everett, Tim, et al.
Publicado: (2022)

Advanced Pedestrian Positioning System to Smartphones and Smartwatches
por: Correa, Alejandro, et al.
Publicado: (2016)

Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance
por: Lehtola, Ville V., et al.
Publicado: (2019)

A GNSS/INS/LiDAR Integration Scheme for UAV-Based Navigation in GNSS-Challenging Environments
por: Elamin, Ahmed, et al.
Publicado: (2022)

Experimental Evaluation of a UWB-Based Cooperative Positioning System for Pedestrians in GNSS-Denied Environment
por: Gabela, Jelena, et al.
Publicado: (2019)

Accurate Spirometry with Integrated Barometric Sensors in Face-Worn Garments
por: Zhou, Bo, et al.
Publicado: (2020)

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity
por: Manivannan, Ajaykumar, et al.
Publicado: (2020)

A dataset of barometric readings for enhancing security and privacy of IoT
por: Ibrahim, Omar Adel, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_uedkqomodun4kbi8qncv7tf17v