Processing String Fusion Approach Investigation for Automated Sea Mine Classification in Shallow Water

Abstract

A novel sea mine computer-aided-detection / computer-aided-classification (CAD/CAC) processing string has been developed. The overall CAD/CAC processing string consists of pre-processing, adaptive clutter filtering (ACF), normalization, detection, feature extraction, feature orthogonalization, optimal subset feature selection, classification and fusion processing blocks. The range-dimension ACF is matched both to average mine highlight and shadow information, while also adaptively suppressing background clutter. For each detected object, features are extracted and processed through an orthogonalization transformation, enabling an efficient application of the optimal log-likelihood-ratio- test (LLRT) classification rule, in the orthogonal feature space domain. The classified objects of 4 distinct processing strings are fused using the classification confidence values as features and "M-out-of-N", or LLRT-based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new shallow water high-resolution sonar imagery data. The processing string detection and classification parameters were tuned and the string classification performance was optimized, by appropriately selecting a subset of the original feature set. Two significant improvements were made to the CAD/CAC processing string by employing sub-image adaptive clutter filtering (SACF) and utilizing a repeated application of the subset feature selection / LLRT classification blocks. It was shown that LLRT-based fusion of the CAD/CAC processing strings outperforms the "M-out-of-N" algorithms and results in up to an eight-fold false alarm rate reduction, compared to the best single CAD/CAC processing string results, while maintaining a constant correct mine classification probability.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2003
Accession Number
ADA498477

Entities

People

  • Gerald Dobeck
  • Manuel Fernandex
  • Tom Aridgides

Organizations

  • Lockheed Martin

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Covariance
  • Data Analysis
  • Data Sets
  • Detection
  • False Alarms
  • Feature Extraction
  • Feature Selection
  • Filters
  • High Resolution
  • Machine Learning
  • Shallow Water
  • Target Classification
  • Target Signatures
  • Unmanned Underwater Vehicles
  • Water

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • Space
  • Space - Space Objects