Target Tracking on Sensing Surface with Electrical Impedance Tomography

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An emerging class of applications uses sensing surfaces, where sensor data is collected from a 2-dimensional surface covering a large spatial area. Sensing surface applications range from observing human activity to detecting failures of construction materials. Electrical impedance tomography (EIT) is an imaging technology, which has been successfully applied to imaging in several important application domains such as medicine, geophysics, and process industry. EIT is a low-cost technology offering high temporal resolution, which makes it a potential technology sensing surfaces. In this paper, we evaluate
the applicability of EIT algorithms for tracking a small moving object on a 2D sensing surface. We compare standard EIT algorithms for this purpose and develop a method which models the movement of a small target on a sensing surface using hidden Markov models (HMM). Existing EIT methods are geared
towards high image quality instead of smooth target trajectories, which makes them suboptimal for target tracking. Numerical experiments indicate that our proposed method outperforms existing EIT methods in target tracking accuracy.
Original languageEnglish
Title of host publication28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings
Number of pages5
ISBN (Electronic)978-9-0827-9705-3
Publication statusPublished - 24 Jan 2021
MoE publication typeA4 Article in a conference publication
EventEuropean Signal Processing Conference - Amsterdam, Netherlands
Duration: 24 Aug 202028 Aug 2020
Conference number: 28

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491
ISSN (Electronic)2076-1465


ConferenceEuropean Signal Processing Conference
Abbreviated titleEUSIPCO


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