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     Research Journal of Applied Sciences, Engineering and Technology


Covariance Intersection Kalman Fuser for Two-Sensor System with Time-Delayed Measurements

1, 2Peng Zhang and 1Zi-Li Deng
1Department of Automation, Heilongjiang University, Harbin, 150080, China
2Department of Computer and Information Engineering, Harbin Deqiang College of Commerce, Harbin 150025, China
Research Journal of Applied Sciences, Engineering and Technology  2013  19:3602-3609
http://dx.doi.org/10.19026/rjaset.6.3566  |  © The Author(s) 2013
Received: December 31, 2012  |  Accepted: February 08, 2013  |  Published: October 20, 2013

Abstract

To handle the estimation fusion problem between local estimation errors for the system with unknown cross-covariances and to avoid a large computed burden and computational complexity of cross-covariances, for a two-sensor linear discrete time-invariant stochastic system with time-delayed measurements, by the measurement transformation method, an equivalent system without measurement delays is obtained and then using the Covariance Intersection (CI) fusion method, the covariance intersection steady-state Kalman fuser is presented. It is proved that its accuracy is higher than that of each local estimator and is lower than that of optimal Kalman fuser weighted by matrices with known cross-covariances. A Monte-Carlo simulation example shows the above accuracy relation and indicates that its actual accuracy is close to that of the Kalman fuser weighted by matrices, hence it has good performances.

Keywords:

Consistency, covariance intersection fusion, information fusion kalman fuser, time-delayed measurement, unknown cross-covariance,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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