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Sensors 2016, 16(8), 1155; doi:10.3390/s16081155

State Estimation for a Class of Non-Uniform Sampling Systems with Missing Measurements

School of Electronics Engineering, Heilongjiang University, Harbin 150080, China
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Author to whom correspondence should be addressed.
Academic Editor: Xuebo Jin
Received: 10 June 2016 / Revised: 13 July 2016 / Accepted: 18 July 2016 / Published: 23 July 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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Abstract

This paper is concerned with the state estimation problem for a class of non-uniform sampling systems with missing measurements where the state is updated uniformly and the measurements are sampled randomly. A new state model is developed to depict the dynamics at the measurement sampling points within a state update period. A non-augmented state estimator dependent on the missing rate is presented by applying an innovation analysis approach. It can provide the state estimates at the state update points and at the measurement sampling points within a state update period. Compared with the augmented method, the proposed algorithm can reduce the computational burden with the increase of the number of measurement samples within a state update period. It can deal with the optimal estimation problem for single and multi-sensor systems in a unified way. To improve the reliability, a distributed suboptimal fusion estimator at the state update points is also given for multi-sensor systems by using the covariance intersection fusion algorithm. The simulation research verifies the effectiveness of the proposed algorithms. View Full-Text
Keywords: modeling; non-uniform sampling; missing measurement; non-augmented estimator; innovation analysis approach modeling; non-uniform sampling; missing measurement; non-augmented estimator; innovation analysis approach
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lin, H.; Sun, S. State Estimation for a Class of Non-Uniform Sampling Systems with Missing Measurements. Sensors 2016, 16, 1155.

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