Abstract ▼ AI-Helper

In order to successfully detect and identify underwater targets located on the seabed, unmanned surface vehicles (USVs) typically acquire acoustic signals with a side-scan sonar device and reconstruct information about the target from the processed images. As the quality of the side-scan sonar image...

In order to successfully detect and identify underwater targets located on the seabed, unmanned surface vehicles (USVs) typically acquire acoustic signals with a side-scan sonar device and reconstruct information about the target from the processed images. As the quality of the side-scan sonar images acquired by USVs depends on the environment and operating parameters, using modeling and simulation techniques to design side-scan sonar devices can help optimize the reconstruction of the sonar images. In this work, we study a side-scan sonar design for use in USVs, that takes the movement of the platform into account. First, we constructed a simulated seabed environment with underwater targets, and specified the maneuvering conditions and sonar systems. We then generated the acoustic signals from the simulated environment using the sonar equation. Finally, we successfully imaged the simulated seabed environment using simple signal processing. Our results can be used to derive USV side-scan sonar design parameters, predict the resulting sonar images in various conditions, and as a basis for determining the optimal sonar parameters of the system.

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