A Combinatorial Approach to Automated Lofargram Analysis

Abstract

This thesis examines the combination of three algorithms: Graph Theoretic Tracker (GTT), Hough Transform, and Heuristic Search to enhance the detection of spectral tracks of underwater targets in LOFARGRAMS. Previous studies examined these algorithms separately. Here, GTT is used as a preprocessor of the LOFARGRAM display data to locate optimum paths of signals through noise. The line tonals in the output image from GTT are then manipulated by the Hough Transform into clusters of points in parameter space. A Heuristic Search sorting technique is employed to points in determine cluster centers. These cluster centers are then reconstructed back into line tonals using the inverse Hough Transform formula. The results of this thesis show improvements by taking the Hough Transform of the original LOFARGRAM masked by the output of GTT. The effect of background noise is offset by the accumulation in the parameter space. Subsequently, the recovery of desired tonals is improved. LOFARGRAM; Graph Theoretic Tracker(GTT); Hough Transform; Heuristic Search; Cluster Analysis; Feature Space; Parameter Space.

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Document Details

Document Type
Technical Report
Publication Date
Jun 18, 1992
Accession Number
ADA255042

Entities

People

  • Vance A. Brahosky

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Background Noise
  • C Programming Language
  • Computer Programming
  • Computer Programs
  • Computer Vision
  • Computers
  • Data Sets
  • Detection
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Image Processing
  • Operating Systems
  • Three Dimensional
  • Two Dimensional
  • United States

Readers

  • Acoustical Oceanography.
  • Computer Vision.
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • Space
  • Space - Space Objects