Sound Classification and Localization Based on Biology Hearing Models and Multiscale Vector Quantization

Abstract

Acoustic Vehicle Classification Objectives and Challenges: 1. Develop systematic methodologies and algorithms; not ad hoc 2. Robust Target ID (with respect to environment, terrain, speed) 3. Algorithms for combined DOA (localization) and target ID 4. Localization assisted ID 5. ID assisted localization 6. Multi-target detection, ID and DOA separation of closely spaced targets 7. Robust feature extraction from auditory models; dynamic DOA and ID 8. Algorithm evaluation in the field and comparison against conventional algorithms for detection, DOA and ID.

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Document Details

Document Type
Technical Report
Publication Date
Aug 24, 1999
Accession Number
ADA512921

Entities

People

  • John Baras

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Acoustic Signals
  • Algorithms
  • Classification
  • Detection
  • Ear
  • Feature Extraction
  • Filters
  • Filtration
  • Frequency
  • Frequency Bands
  • Identification
  • Neural Networks
  • Recognition
  • Sensor Networks
  • Spectra
  • Supervised Machine Learning
  • Target Detection

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Phased Array Antenna Design.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • Space
  • Space - Space Objects