Cargando…
Multi-Sensor Fusion for Underwater Vehicle Localization by Augmentation of RBF Neural Network and Error-State Kalman Filter
The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF) are widely used in underwater multi-sensor fusion applications for localization and navigation. Since these filters are designed by employing first-order Taylor series approximation in the error covariance m...
Autores principales: | Shaukat, Nabil, Ali, Ahmed, Javed Iqbal, Muhammad, Moinuddin, Muhammad, Otero, Pablo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916077/ https://www.ncbi.nlm.nih.gov/pubmed/33562145 http://dx.doi.org/10.3390/s21041149 |
Ejemplares similares
-
Underwater Vehicle Positioning by Correntropy-Based Fuzzy Multi-Sensor Fusion
por: Shaukat, Nabil, et al.
Publicado: (2021) -
Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles
por: Zhang, Fubin, et al.
Publicado: (2022) -
An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering
por: Luo, Qinghua, et al.
Publicado: (2020) -
An Augmented Reality Based Human-Robot Interaction Interface Using Kalman Filter Sensor Fusion
por: Li, Chunxu, et al.
Publicado: (2019) -
A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation
por: Vargas-Meléndez, Leandro, et al.
Publicado: (2016)