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Ocean Systems Engineering Volume 10, Number 4, December 2020 , pages 435-449 DOI: https://doi.org/10.12989/ose.2020.10.4.435 |
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Sonar-based yaw estimation of target object using shape prediction on viewing angle variation with neural network |
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Minsung Sung and Son-Cheol Yu
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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. | ||
| Key Words | ||
| sonar GAN; underwater GAN; object detection; sonar simulator; underwater sonar image; underwater object detection; acoustic landmark | ||
| Address | ||
| Minsung Sung and Son-Cheol Yu: Department of IT Engineering, Pohang University of Science and Technology (POSTECH), 77 Cheongam-ro, Nam-gu, Pohang, Republic of Korea | ||
