Non-redundant high-integrity position estimation robust to sensor bias jumps using MGLR

Non-redundant high-integrity position estimation robust to sensor bias jumps using MGLR

This paper presents and experimentally evaluates an algorithm named Multiple Generalized Likelihood Ratio (MGLR) for detecting and estimating multiple consecutive measurement biases appearing frequently, in the case of non-redundant sensors; typically the case for a small drone or remotely piloted a...

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Bibliographic Details
Main Authors: Gustav Öman Lundin, Philippe Mouyon, Augustin Manecy, Gustaf Hendeby
Format: Article
Language:English
Published: Canadian Science Publishing 2022-01-01
Series:Drone Systems and Applications
Subjects:
position estimation
GLR
non-redundant measurements
integrity
estimation de position
rapport de vraisemblance généralisé (« GLR »)
Online Access:https://cdnsciencepub.com/doi/10.1139/dsa-2022-0010

Internet

https://cdnsciencepub.com/doi/10.1139/dsa-2022-0010

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