Ocean Systems Engineering

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Sonar-based yaw estimation of target object using shape prediction on viewing angle variation with neural network

  • Sung, Minsung (Department of IT Engineering, Pohang University of Science and Technology (POSTECH)) ;
  • Yu, Son-Cheol (Department of IT Engineering, Pohang University of Science and Technology (POSTECH))
  • Received : 2020.09.11
  • Accepted : 2020.12.02
  • Published : 2020.12.25
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Abstract

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

Keywords

Acknowledgement

This research was a part of the project titled 'Gyeongbuk Sea Grant', funded by the Ministry of Oceans and Fisheries, Korea.

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