Open AccessBook
Fundamentals of high accuracy inertial navigation
TLDR
In this article, a central force gravity field model is used for inertial navigation with assistance from external measurements. But this model is not suitable for the Kalman Filter State Variable Error Models.Citations
More filters
Proceedings ArticleDOI
A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation
TL;DR: The primary contribution of this work is the derivation of a measurement model that is able to express the geometric constraints that arise when a static feature is observed from multiple camera poses, and is optimal, up to linearization errors.
Journal ArticleDOI
Adaptive Kalman Filtering for INS/GPS
Ahmed Mohamed,K. P. Schwarz +1 more
TL;DR: The detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given, based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors.
Journal ArticleDOI
Visual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration
TL;DR: This paper describes an algorithm, based on the unscented Kalman filter, for self-calibration of the transform between a camera and an inertial measurement unit (IMU), which demonstrates accurate estimation of both the calibration parameters and the local scene structure.
Journal ArticleDOI
In-Car Positioning and Navigation Technologies—A Survey
Isaac Skog,Peter Händel +1 more
TL;DR: A survey of the information sources and information fusion technologies used in current in-car navigation systems is presented and the pros and cons of the four commonly used information sources are described.
Book
Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Second Edition
TL;DR: The second edition of the Artech House book Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems as discussed by the authors offers a current and comprehensive understanding of satellite navigation, inertial navigation, terrestrial radio navigation, dead reckoning, and environmental feature matching.