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DOI: 10.14569/IJACSA.2011.021206
PDF

Outlier-Tolerant Kalman Filter of State Vectors in Linear Stochastic System

Author 1: HU Shaolin
Author 2: Huajiang Ouyang
Author 3: Karl Meinke
Author 4: SUN Guoji

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 12, 2011.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The Kalman filter is widely used in many different fields. Many practical applications and theoretical results show that the Kalman filter is very sensitive to outliers in a measurement process. In this paper some reasons why the Kalman Filter is sensitive to outliers are analyzed and a series of outlier-tolerant algorithms are designed to be used as substitutes of the Kalman Filter. These outlier-tolerant filters are highly capable of preventing adverse effects from outliers similar with the Kalman Filter in complexity degree and very outlier-tolerant in the case there are some outliers arisen in sampling data set of linear stochastic systems. Simulation results show that these modified algorithms are safe and applicable.

Keywords: Kalman filter; Outlier-tolerant; Outlier; Linear stochastic system.

HU Shaolin, Huajiang Ouyang, Karl Meinke and SUN Guoji, “Outlier-Tolerant Kalman Filter of State Vectors in Linear Stochastic System” International Journal of Advanced Computer Science and Applications(IJACSA), 2(12), 2011. http://dx.doi.org/10.14569/IJACSA.2011.021206

@article{Shaolin2011,
title = {Outlier-Tolerant Kalman Filter of State Vectors in Linear Stochastic System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.021206},
url = {http://dx.doi.org/10.14569/IJACSA.2011.021206},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {12},
author = {HU Shaolin and Huajiang Ouyang and Karl Meinke and SUN Guoji}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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