Cargando…
An Unsupervised Learning Technique to Optimize Radio Maps for Indoor Localization
A major burden of signal strength-based fingerprinting for indoor positioning is the generation and maintenance of a radio map, also known as a fingerprint database. Model-based radio maps are generated much faster than measurement-based radio maps but are generally not accurate enough. This work pr...
Autores principales: | Trogh, Jens, Joseph, Wout, Martens, Luc, Plets, David |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412762/ https://www.ncbi.nlm.nih.gov/pubmed/30781755 http://dx.doi.org/10.3390/s19040752 |
Ejemplares similares
-
Multi-Floor Indoor Pedestrian Dead Reckoning with a Backtracking Particle Filter and Viterbi-Based Floor Number Detection
por: De Cock, Cedric, et al.
Publicado: (2021) -
LoRaWAN Geo-Tracking Using Map Matching and Compass Sensor Fusion †
por: Podevijn, Nico, et al.
Publicado: (2020) -
Use of Machine Learning for the Estimation of Down‐ and Up‐Link Field Exposure in Multi‐Source Indoor WiFi Scenarios
por: Tognola, Gabriella, et al.
Publicado: (2021) -
Robust IMU-Based Mitigation of Human Body Shadowing in UWB Indoor Positioning
por: De Cock, Cedric, et al.
Publicado: (2023) -
Impact of a Small Cell on the RF-EMF Exposure in a Train
por: Aerts, Sam, et al.
Publicado: (2015)