Low-Frequency Active Target Characterization Using Hidden Markov Models and Classifiers.

Abstract

We investigate various projection spaces and extract key parameters or features from each space to characterize low-frequency active (LFA) target returns in a low-dimensional space. The projection spaces encompass (1) time embedded phase map, (2) segmented matched filter output, (3) various time frequency distribution functions, such as Reduced Interference Distribution, to capture time-varying echo signatures, and (4) principal component inversion for signal cleaning and characterization. We utilize both dynamic and static features and parameterize them with a hybrid classification methodology consisting of hidden Markov models, classifiers, and data fusion. This clue identification and evaluation process is complemented by concurrent work on target physics to enhance our understanding of the target echo formation process. As a function of target aspect, we can observe (1) back scatter dominated by axial n=O modes propagating back and forth along the length of the shell, (2) direct scatter from shell discontinuities, (3) helical or creeping waves from phase matching between the acoustic waves and membrane waves (both shear and compressional), and (4) the "array response" of the shell, with coherent super- position of elemental scattering sites along the shell leading to a peak response near broadside. As a function of target structures (the empty shell and the ribbed/complex shells), we see considerable complexity brought about by multiple reflections of the membrane waves between the rings. We show the merit of fusing parameters estimated from these projection spaces in characterizing LFA target returns using the MIT/NRL scaled model data. Our hybrid classifiers outperform the matched filter-based recognizer by an average of 5 to 25%.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA300872

Entities

People

  • David H. Kil
  • Frances B. Shin
  • J. R. Fricke

Organizations

  • Lockheed Martin

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustics
  • Algorithms
  • Coding
  • Data Analysis
  • Data Compression
  • Detection
  • Discriminant Analysis
  • Feature Extraction
  • Hidden Markov Models
  • Information Science
  • Markov Models
  • Neural Networks
  • Pattern Recognition
  • Probability
  • Recognition
  • Signal Processing
  • Topology

Readers

  • Computer Vision.
  • Radar Systems Engineering.
  • Structural Dynamics.

Technology Areas

  • Space
  • Space - Space Objects