Dynamic Electrical Impedance Tomography with Known Internal Structures

Abstract

A dynamic (time-varying) electrical impedance tomography (EIT) imaging technique is described for the cases in which a fixed internal structure and/or its resistivity are known and the resistivity distribution of the rest of the interior of the object changes rapidly within the time taken to acquire a full set of independent measurement data. The inverse problem is treated as the state estimation problem and the unknown state (resistivity) is estimated with the aid of the extended Kalman filter (EKF) in a minimum mean square error sense. In doing so, additional information for the known internal structure and/or its resistivity is incorporated into the cost functional as prior information and modified Tikhonov regularization technique is utilized. We carried out both computer simulations with synthetic data and laboratory experiment with real measurement data to illustrate the reconstruction performance of the proposed algorithm.

Keywords:

• Dynamic Reconstruction
• Electrical Impedance Tomography
• Extended Kalman Filter
• Internal Structure
• Prior Information
• Tikhonov Regularization