Quantitative analysis of observability in linear time-varying systems

Kai Shen; Andrey V. Proletarsky; Konstantin A. Neusypin

doi:10.1109/ChiCC.2016.7553058

Quantitative analysis of observability in linear time-varying systems

Kai Shen, Andrey V. Proletarsky, Konstantin A. Neusypin

Bauman Moscow State Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

The general observability theory of linear time-varying systems was introduced. Definitions of local observability and local observability matrix were further made, accordingly. In order to test the observability of a system, a local observability criterion for linear time-varying systems was derived. Moreover, the degree of observability was formulated based on Kalman observability theory in order to know how state-variables are observed. The application of proposed observability analysis methods to integrated navigation systems showed that the degree of observability of velocity errors is better than that of misalignment angles and even better than that of drift rates; the normalized degree of observability may serve as a quantitative criterion for information fusion of navigation sensors.

Original language	English
Title of host publication	Proceedings of the 35th Chinese Control Conference, CCC 2016
Editors	Jie Chen, Qianchuan Zhao, Jie Chen
Publisher	IEEE Computer Society
Pages	44-49
Number of pages	6
ISBN (Electronic)	9789881563910
DOIs	https://doi.org/10.1109/ChiCC.2016.7553058
Publication status	Published - 26 Aug 2016
Externally published	Yes
Event	35th Chinese Control Conference, CCC 2016 - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016

Publication series

Name	Chinese Control Conference, CCC
Volume	2016-August
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	35th Chinese Control Conference, CCC 2016
Country/Territory	China
City	Chengdu
Period	27/07/16 → 29/07/16

Keywords

Degree of observability
Integrated navigation system
Linear time-varying system
Quantitative analysis of observability

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10.1109/ChiCC.2016.7553058

Cite this

Shen, K., Proletarsky, A. V., & Neusypin, K. A. (2016). Quantitative analysis of observability in linear time-varying systems. In J. Chen, Q. Zhao, & J. Chen (Eds.), Proceedings of the 35th Chinese Control Conference, CCC 2016 (pp. 44-49). Article 7553058 (Chinese Control Conference, CCC; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/ChiCC.2016.7553058

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title = "Quantitative analysis of observability in linear time-varying systems",

abstract = "The general observability theory of linear time-varying systems was introduced. Definitions of local observability and local observability matrix were further made, accordingly. In order to test the observability of a system, a local observability criterion for linear time-varying systems was derived. Moreover, the degree of observability was formulated based on Kalman observability theory in order to know how state-variables are observed. The application of proposed observability analysis methods to integrated navigation systems showed that the degree of observability of velocity errors is better than that of misalignment angles and even better than that of drift rates; the normalized degree of observability may serve as a quantitative criterion for information fusion of navigation sensors.",

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author = "Kai Shen and Proletarsky, \{Andrey V.\} and Neusypin, \{Konstantin A.\}",

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year = "2016",

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day = "26",

doi = "10.1109/ChiCC.2016.7553058",

language = "English",

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Shen, K, Proletarsky, AV & Neusypin, KA 2016, Quantitative analysis of observability in linear time-varying systems. in J Chen, Q Zhao & J Chen (eds), Proceedings of the 35th Chinese Control Conference, CCC 2016., 7553058, Chinese Control Conference, CCC, vol. 2016-August, IEEE Computer Society, pp. 44-49, 35th Chinese Control Conference, CCC 2016, Chengdu, China, 27/07/16. https://doi.org/10.1109/ChiCC.2016.7553058

Quantitative analysis of observability in linear time-varying systems. / Shen, Kai; Proletarsky, Andrey V.; Neusypin, Konstantin A.
Proceedings of the 35th Chinese Control Conference, CCC 2016. ed. / Jie Chen; Qianchuan Zhao; Jie Chen. IEEE Computer Society, 2016. p. 44-49 7553058 (Chinese Control Conference, CCC; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The general observability theory of linear time-varying systems was introduced. Definitions of local observability and local observability matrix were further made, accordingly. In order to test the observability of a system, a local observability criterion for linear time-varying systems was derived. Moreover, the degree of observability was formulated based on Kalman observability theory in order to know how state-variables are observed. The application of proposed observability analysis methods to integrated navigation systems showed that the degree of observability of velocity errors is better than that of misalignment angles and even better than that of drift rates; the normalized degree of observability may serve as a quantitative criterion for information fusion of navigation sensors.

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Quantitative analysis of observability in linear time-varying systems

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