Study and Design of Bayesian Methods for GNSS in Challenging Environments

L'abstract è presente nell'allegato / the abstract is in the attachment

Grantor dc:publisher

Politecnico di Torino

Year dc:date

2025

Author dc:creator

• VOUCH, OLIVIERO

Contributors dc:contributor

• DOVIS, FABIO

• Global Navigation Satellite System
• Bayesian Estimation
• Kalman Filtering
• Particle Filtering
• ultra-wide band
• Sensor Integration
• Collaborative Positioning
• Deep Space Navigation
• Orbit Determination
• Lunar GNSS Receiver Experiment
• Autonomous Navigation
• Trajectory-Aware Estimation
• Settore IINF-03/A - Telecomunicazioni

Statement dc:rights

• info:eu-repo/semantics/openAccess
• license:Creative commons
• license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language

eng

Identifier

http://dx.doi.org/10.13121/polito/porto/3003997
10.13121/polito/porto/3003997

OAI identifier oai:identifier

oai:iris.polito.it:11583/3003997