Statistical Sensor Fusion

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Using Inertial Sensors for Position and Orientation Estimation (2017, unknown): “For the problem of position and orientation estimation using inertial sensors, there are two commonly used modeling alternatives for the dynamics [50].”
Some Relations Between Extended and Unscented Kalman Filters (2012, background): “Given the transformed sigma-points in (15), the terms in Algorithm 1 involving Jacobians and Hessians can be approximated arbitrarily well as with Further, for a scalar ,”
A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation (2018, methodology): “To improve system performance in terms of reliability of the estimates (integrity), accuracy, and availability, it is appealing to process information obtained from a number of sensors by means of fusion techniques [131], [132].”
FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing (2020, methodology): “A promising way to solve such issues from the algorithmic perspective is to use robust distributed optimization [149], [150], robust estimation [151], and robust fusion [132] techniques for remedy.”