Spatial and Temporal Independent Component Analysis Of Micro-Doppler Features

Abstract

Micro-Doppler features can be regarded as a unique signature of an object with movements and provide additional information for classification, recognition and identification of the object. Independent component analysis (ICA) can decompose micro-Doppler features into independent basis functions that represent salient physical movement attributes of the object. To study ICA of micro-Doppler features, we used a dataset generated by simulation of radar returned signals from rotating objects and tumbling objects. Fast ICA algorithm was used in our study to decompose micro-Doppler features into a set of spatial and temporal independent components. Spatial characteristics of the independent components combined with the corresponding temporal characteristics can be used to improve performance of classification, recognition and identification.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA497528

Entities

People

  • Victor C. Chen

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coordinate Systems
  • Data Sets
  • Doppler Effect
  • Electrical Engineering
  • Euler Angles
  • Feature Extraction
  • Frequency
  • Frequency Domain
  • Frequency Modulation
  • Frequency Shift
  • Identification
  • Image Processing
  • Military Research
  • Recognition
  • Simulations
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Radar Systems Engineering.
  • Theoretical Analysis.