An efficient tuning framework for Kalman filter parameter optimization using design of experiments and genetic algorithms-Reference-Cited by-同舟云学术

An efficient tuning framework for Kalman filter parameter optimization using design of experiments and genetic algorithms

Published:2020-10-22 Issue:4 Volume:67 Page:775-793
ISSN:0028-1522
Container-title:NAVIGATION
language:en
Short-container-title:Navigation

Author:

Zhang Alan¹^ORCID,Atia Mohamed Maher¹^ORCID

Affiliation:

1. Department of Systems and Computer Engineering Carleton University Embedded and Multi‐sensor Systems Lab Carleton University 1125 Colonel By Drive Ottawa ON K1S 5B6 Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Navigation

Subject

Electrical and Electronic Engineering,Aerospace Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/navi.399

Reference19 articles.

1. Multi-Sensor Integrated Navigation in Urban and Indoor Environments

2. Numerical comparison of kalman filter algorithms: Orbit determination case study

3. Chiu D. S. &O'Keffe K. P.(2008 January).Bierman‐Thornton UD filtering for double‐differenced carrier phase estimation accounting for full mathematical correlation.Proceedings of the 2008 National Technical Meeting of The Institute of Navigation San Diego CA 756–762.

4. The $\chi^2$ Test of Goodness of Fit

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