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비선형 보간법을 이용한 수중 이미지 소나의 3 차원 해저지형 실시간 생성기법

Real-time Data Enhancement of 3D Underwater Terrain Map Using Nonlinear Interpolation on Image Sonar

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참고문헌

키워드

주제분류공학일반

초록

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

Abstract

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

참고문헌 (13)

  1. M. Qadri, "Neural Implicit Surface Reconstruction Using Imaging Sonar", arXiv, 08221~ (2022)
  2. S. Royo, "An Overview of Lidar Imaging Systems for Autonomous Vehicles", Appl. Sci., 9(19), pp.4093~ (2019)
  3. Hodges, R. P., "Underwater Acoustics: Analysis, Design, and Performance of Sonar", pp.1~15 (2010), J. Wiley
  4. E. Belcher, "Dual-Frequency Identification Sonar (Didson)", Proc. of 2002 Int. Symp. Underwater Technol, pp.187~192 (2022)
  5. D. T. Blackstock, "Fundamentals of Physical Acoustics", pp.1274~1276 (2000), Wiley
  6. I. Ashraf, "An Investigation of Interpolation Techniques to Generate 2d Intensity Image from Lidar Data", IEEE Access, 5, pp.8250~8260 (2017)
  7. E. Galceran, "A Survey on Coverage Path Planning for Robotics", Robot. Auton. Syst., 61(12), pp.1258~1276 (2013)
  8. I. Amidror, "Scattered Data Interpolation Methods for Electronic Imaging Systems: A Survey", J. Electron. Imag., 11(2), pp.157~176 (2002)
  9. H. Cho, "Auv-Based Underwater 3-D Point Cloud Generation Using Acoustic Lens-Based Multibeam Sonar", IEEE J. Ocean. Eng., 43(4), pp.856~872 (2018)
  10. C. H. Sherman, "Transducers and Arrays for Underwater Sound", pp.122~126 (2007), Springer Publishing Company
  11. C. Fritsch, "A Multirate Scan Conversion Method", Ultrason., 38(1), pp.179~182 (2000)
  12. J. M. Bell, "Simulation and Analysis of Synthetic Sidescan Sonar Images", IEE Proc. - Radar, Sonar Navig., 144(4), pp.219~226 (1997)

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