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A Comparison of Outlier Detection Procedures and Robust Estimation Methods in GPS Positioning

Published online by Cambridge University Press:  07 October 2009

Nathan L. Knight  and
Jinling Wang
Nathan L. Knight*
Affiliation:
(The University of New South Wales, Sydney, Australia)
Jinling Wang
Affiliation:
(The University of New South Wales, Sydney, Australia)
*
(Email: N.Knight@student.unsw.edu.au)
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Abstract

With more satellite systems becoming available there is currently a need for Receiver Autonomous Integrity Monitoring (RAIM) to exclude multiple outliers. While the single outlier test can be applied iteratively, in the field of statistics robust methods are preferred when multiple outliers exist. This study compares the outlier test and numerous robust methods with simulated GPS measurements to identify which methods have the greatest ability to correctly exclude outliers. It was found that no method could correctly exclude outliers 100% of the time. However, for a single outlier the outlier test achieved the highest rates of correct exclusion followed by the MM-estimator and the L1-norm. As the number of outliers increased MM-estimators and the L1-norm obtained the highest rates of normal exclusion, which were up to ten percent higher than the outlier test.

Keywords

RAIMOutliersRobustIntegrity

Information

Type
Research Article
Information
The Journal of Navigation , Volume 62 , Issue 4 , October 2009 , pp. 699 - 709
Copyright
Copyright © The Royal Institute of Navigation 2009

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