Principles of GNSS, Inertial, and Multi-Sensor Integrated Navigation Systems

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Robust and Precise Vehicle Localization Based on Multi-Sensor Fusion in Diverse City Scenes (2017, methodology): “alibrated out with observations from a surveyed reference station. The carrier-phase based differential GNSS technique, known as Real Time Kinematic (RTK), can provide centimeter positioning accuracy [1]. The most signiﬁcant advantage of RTK is that it provides almost all-weather availability. Howev”
GNSS Position Integrity in Urban Environments: A Review of Literature (2018, unknown): “The KF [128] (and its variants such as the extended Kalman filter [73]) is one of the most celebrated and popular data fusion algorithms.”
A Theoretical Foundation of Network Localization and Navigation (2018, background): “Those measurements provide the information about the state evolution over different instants and can significantly benefit localization through a filtering process [77]–[81].”
Pedestrian localisation for indoor environments (2008, methodology): “These include the federated zero-reset architecture, in which the state of the first filter is zeroed following input to the second filter, with the corresponding elements of the first filter’s covariance matrix reset to their initialisation values [18].”