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A High-Efficiency Side-Scan Sonar Simulator for High-Speed Seabed Mapping.

Xiangjian MengWen XuBinjian ShenXinxin Guo
Published in: Sensors (Basel, Switzerland) (2023)
Side scan sonar (SSS) is a multi-purpose ocean sensing technology, but due to the complex engineering and variable underwater environment, its research process often faces many uncertain obstacles. A sonar simulator can provide reasonable research conditions for guiding development and fault diagnosis, by simulating the underwater acoustic propagation and sonar principle to restore the actual experimental scenarios. However, the current open-source sonar simulators gradually lag behind mainstream sonar technology; therefore, they cannot be of sufficient assistance, especially due to their low computational efficiency and unsuitable high-speed mapping simulation. This paper presents a sonar simulator based on a two-level network architecture, which has a flexible task scheduling system and extensible data interaction organization. The echo signal fitting algorithm proposes a polyline path model to accurately capture the propagation delay of the backscattered signal under high-speed motion deviation. The large-scale virtual seabed is the operational nemesis of the conventional sonar simulators; therefore, a modeling simplification algorithm based on a new energy function is developed to optimize the simulator efficiency. This paper arranges several seabed models to test the above simulation algorithms, and finally compares the actual experiment results to prove the application value of this sonar simulator.
Keyphrases
  • high speed
  • atomic force microscopy
  • virtual reality
  • high resolution
  • machine learning
  • high efficiency
  • computed tomography
  • deep learning
  • magnetic resonance
  • artificial intelligence
  • climate change
  • diffusion weighted