Advanced Kalman Filtering Approaches to Bayesian State Estimation

Advanced Kalman Filtering Approaches to Bayesian State Estimation

Bayesian state estimation is a flexible framework to address relevant problems at the heart of existing and upcoming technologies. Application examples are obstacle tracking for driverless cars and indoor navigation using smartphone sensor data. Unfortunately, the mathematical solutions of the under...

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Bibliographic Details
Main Author: Roth, Michael
Format: Doctoral Thesis
Language:English
Published: Linköpings universitet, Reglerteknik 2017
Subjects:
Signal Processing
Signalbehandling
Control Engineering
Reglerteknik
Computational Mathematics
Beräkningsmatematik
Computer Science
Datavetenskap (datalogi)
Probability Theory and Statistics
Sannolikhetsteori och statistik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-134867
http://nbn-resolving.de/urn:isbn:9789176855782

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-134867
http://nbn-resolving.de/urn:isbn:9789176855782

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