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Sensors 2017, 17(4), 924; doi:10.3390/s17040924

State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement

1
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
2
School of Engineering, Huzhou University, Huzhou 310027, China
*
Author to whom correspondence should be addressed.
Received: 15 February 2017 / Revised: 18 April 2017 / Accepted: 19 April 2017 / Published: 21 April 2017
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Abstract

Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in some practical applications, engineers can only get the range of noises, instead of the precise statistical distributions. Hence, in the framework of Dempster-Shafer (DS) evidence theory, a novel state estimatation method by fusing dependent evidence generated from state equation, observation equation and the actual observations of the system states considering bounded noises is presented. It can be iteratively implemented to provide state estimation values calculated from fusion results at every time step. Finally, the proposed method is applied to a low-frequency acoustic resonance level gauge to obtain high-accuracy measurement results. View Full-Text
Keywords: DS evidence theory; state estimation; liquid level measurement; alarm monitoring DS evidence theory; state estimation; liquid level measurement; alarm monitoring
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Xu, X.; Li, Z.; Li, G.; Zhou, Z. State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement. Sensors 2017, 17, 924.

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