Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning

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Sillanpää , T O N , Longi , K E , Mäkinen , J M K , Rauhala , T , Klami , A , Salmi , A & Haeggström , E 2021 , ' Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning ' , AIP Advances , vol. 11 , no. 11 , 115104 . https://doi.org/10.1063/5.0068803

Title: Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning
Author: Sillanpää, Tom Oskar Nikolai; Longi, Krista Elena; Mäkinen, Joni Mikko Kristian; Rauhala, Timo; Klami, Arto; Salmi, Ari; Haeggström, Edward
Contributor organization: Division of Pharmaceutical Chemistry and Technology
Materials Physics
Department of Physics
Multi-source probabilistic inference research group / Arto Klami
Department of Computer Science
Helsinki Institute for Information Technology
Date: 2021
Language: eng
Number of pages: 11
Belongs to series: AIP Advances
ISSN: 2158-3226
DOI: https://doi.org/10.1063/5.0068803
URI: http://hdl.handle.net/10138/335988
Abstract: Ultrasound is employed in, e.g., non-destructive testing and environmental sensing. Unfortunately, conventional single-element ultrasound probes have a limited acoustic aperture. To overcome this limitation, we employ a modern method to increase the field-of-view of a commercial transducer and to test the approach by localizing a target. In practice, we merge the transducer with a chaotic cavity to increase the effective aperture of the transducer. In conventional pulse-echo ultrasound signal analysis, location estimation is based on determining the time-of-flight with known propagation speed in the medium. In the present case, the dispersing field induces complexity to this inverse problem, also in 2D. To tackle this issue, we use a convolutional neural network-based machine learning approach to study the feasibility of employing one single chaotic cavity transducer to localize an object in 2D. We show that we indeed can localize an inclusion inside a water-filled cylinder. The localization accuracy is one diameter of the inclusion. The area that we can infer increases by 49% in comparison to using the same transducer without applying the proposed chaotic cavity method. (C) 2021 Author(s).
Subject: 113 Computer and information sciences
TIME-REVERSAL
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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