Systematic error modeling and bias estimation

Feihu Zhang; Alois Knoll

doi:10.3390/s16050729

Systematic error modeling and bias estimation

Feihu Zhang, Alois Knoll

Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems

Technical University of Munich

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

This paper analyzes the statistic properties of the systematic error in terms of range and bearing during the transformation process. Furthermore, we rely on a weighted nonlinear least square method to calculate the biases based on the proposed models. The results show the high performance of the proposed approach for error modeling and bias estimation.

Original language	English
Article number	729
Journal	Sensors (Switzerland)
Volume	16
Issue number	5
DOIs	https://doi.org/10.3390/s16050729
State	Published - May 2016

Keywords

Bias
Least square method
Systematic error

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10.3390/s16050729

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title = "Systematic error modeling and bias estimation",

abstract = "This paper analyzes the statistic properties of the systematic error in terms of range and bearing during the transformation process. Furthermore, we rely on a weighted nonlinear least square method to calculate the biases based on the proposed models. The results show the high performance of the proposed approach for error modeling and bias estimation.",

keywords = "Bias, Least square method, Systematic error",

author = "Feihu Zhang and Alois Knoll",

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KW - Least square method

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Systematic error modeling and bias estimation

Abstract

Keywords

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