Image reconstruction in time-varying electrical impedance tomographybased on the extended Kalman filter

Abstract

In electrical impedance tomography (EIT), the resistivity(conductivity) distribution of the unknown object is estimated from boundaryvoltages induced by different current patterns with the aid of variousreconstruction algorithms. In this paper, we propose an EIT imagereconstruction algorithm based on the extended Kalman filter (EKF) to estimaterapidly time-varying changes in resistivity occurring within the time taken toacquire a full set of independent measurement data. The EIT inverseproblem is formulated as a state estimation problem in which the system ismodelled with the state equation and the observation equation. The unknowntime-varying state (resistivity) is estimated with the aid of the EKF. Bothcomputer simulations with synthetic data and experiments with real measurementdata are provided to illustrate the reconstruction performance of the proposedalgorithm.