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Updated: Jun 21, 2026

Image-based Lagrangian Particle Tracking in Bed-load Experiments
Published on: July 20, 2017
Unscented Kalman filter approach to tracking a moving interfacial boundary in sedimentation processes using
Anil Kumar Khambampati1, Ahmar Rashid, Umer Zeeshan Ijaz
1Department of Electrical and Electronic Engineering, Cheju National University, Cheju 690-756, South Korea.
Abstract:
The monitoring of solid-fluid suspensions under the influence of gravity is widely used in industrial processes. By considering sedimentation layers with different electrical properties, non-invasive methods such as electrical impedance tomography (EIT) can be used to estimate the settling curves and velocities. In recent EIT studies, the problem of estimating the locations of phase interfaces and phase conductivities has been treated as a nonlinear state estimation problem and the extended Kalman filter (EKF) has been successfully applied. However, the EKF is based on a Gaussian assumption and requires a linearized measurement model. The linearization (or derivation of the Jacobian) is possible when there are no discontinuities in the system. Furthermore, having a complex phase interface representation makes derivation of the Jacobian a tedious task. Therefore, in this paper, we explore the unscented Kalman filter (UKF) as an alternative approach for estimating phase interfaces and conductivities in sedimentation processes. The UKF uses a nonlinear measurement model and is therefore more accurate. In order to justify the proposed approach, extensive numerical experiments have been performed and a comparative analysis with the EKF is provided.
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