Cargando…
MLCA—A Machine Learning Framework for INS Coarse Alignment
Inertial navigation systems provides the platform’s position, velocity, and attitude during its operation. As a dead-reckoning system, it requires initial conditions to calculate the navigation solution. While initial position and velocity vectors are provided by external means, the initial attitude...
Autores principales: | Zak, Idan, Katz, Reuven, Klein, Itzik |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731381/ https://www.ncbi.nlm.nih.gov/pubmed/33291421 http://dx.doi.org/10.3390/s20236959 |
Ejemplares similares
-
Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements
por: Tal, Asaf, et al.
Publicado: (2017) -
Coarse Alignment of Marine Strapdown INS Based on the Trajectory Fitting of Gravity Movement in the Inertial Space
por: Zhao, Lin, et al.
Publicado: (2016) -
Observability Analysis of DVL/PS Aided INS for a Maneuvering AUV
por: Klein, Itzik, et al.
Publicado: (2015) -
GNSS/INS Fusion with Virtual Lever-Arm Measurements
por: Borko, Aviram, et al.
Publicado: (2018) -
Coarse-grained versus fully atomistic machine learning for zeolitic imidazolate frameworks
por: Faure Beaulieu, Zoé, et al.
Publicado: (2023)