Resolution Dependence of Acoustic Scatterings Statistics For Complex Seafloors

Abstract

Unmanned underwater vehicles (UUVs) utilize sonar perception to conduct sea floor mapping and target detection operations. However, systems with different resolutions may generate different probability density functions (PDFs) of the magnitude of the complex pressure. An area of research that has not been adequately studied is the effects of resolution manipulation during the post-processing of high-resolution data from complex seafloor environments. This work analyzed synthetic aperture sonar (SAS) data collected from multiple seafloor geomorphologies surrounding Bergen, Norway, to study the resolution dependence of scattering statistics for complex seafloors. Multi-look methods were applied to reduce the resolution. The original data and reduced resolution data were compared in terms of PDF amplitude and evaluated by standard goodness of fit tests with heavy-tailed statistical models that are commonly used in the radar and sonar community, including mixture models. Top-performing physics-based distributions were analyzed by how well they model how background and clutter parameters change with resolution manipulation. Empirical equations and a table of environmental constants were developed to allow a user to understand better how sonar data behaves at a given resolution and bottom type.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2022
Accession Number
AD1185015

Entities

People

  • Alexander J. Lehman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Counter WMD

DTIC Thesaurus Topics

  • Acoustic Scattering
  • Autonomous Underwater Vehicles
  • Backscattering
  • California
  • Data Sets
  • Detection
  • Goodness Of Fit Tests
  • High Resolution
  • Information Science
  • Probability
  • Probability Density Functions
  • Scattering
  • Seabed
  • Standards
  • Statistics
  • Surveys
  • Synthetic Aperture Sonar
  • Target Detection
  • Underwater Vehicles
  • Unmanned Underwater Vehicles
  • Unmanned Vehicles

Readers

  • Acoustical Oceanography.
  • Radar Systems Engineering.
  • Statistical inference.

Technology Areas

  • Autonomy