Multiscale Signal Processing and Shape Analysis for an Inverse Sar Imaging System

Abstract

The great challenge in signal processing is to devise computationally efficient and statistically optimal algorithms for estimating signals from noisy background and understanding their contents. This thesis treats the problem of multiscale signal processing and shape analysis for an Inverse Synthetic Aperture Radar (ISAR) imaging system. To address some of the limitations of conventional techniques in radar image processing, an information theoretic approach for target motion estimation is first proposed. A wavelet based multiscale method for shape enhancement is subsequently derived and followed by a regression technique for shape recognition.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2001
Accession Number
ADA460126

Entities

People

  • Yun He

Organizations

  • North Carolina State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computer Vision
  • Detectors
  • Electrical Engineering
  • Engineering
  • Feature Extraction
  • Filters
  • Filtration
  • Geometry
  • Image Processing
  • Image Registration
  • Information Theory
  • Mathematical Filters
  • Radar
  • Signal Processing
  • Synthetic Aperture Radar
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Radar Systems Engineering.