Target Tracking with Electrical Impedance Tomography

TL;DR

This paper introduces a novel approach combining electrical impedance tomography with hidden Markov models to improve the accuracy of tracking moving targets on conductive surfaces.

Contribution

The paper presents a new method that integrates EIT with hidden Markov models, optimizing for smooth target trajectories rather than image quality.

Findings

Proposed method outperforms existing EIT techniques in tracking accuracy.

Numerical experiments demonstrate improved target localization.

Method achieves high temporal resolution for real-time tracking.

Abstract

Electrical impedance tomography (EIT) has been successfully applied to several important application domains such as medicine, geophysics and industrial imaging. EIT offers a high temporal resolution, which allows to track the location of a moving target on a conductive surface accurately. Existing EIT methods are geared towards high image quality instead of smooth target trajectories, which makes them suboptimal for target tracking. We combine EIT methods with hidden Markov models for tracking moving targets on a conductive surface. Numerical experiments indicate that the proposed method outperforms existing EIT methods in target tracking accuracy.