Focusing ISAR Images using Fast Adaptive Time-Frequency and 3D Motion Detection on Simulated and Experimental Radar Data

Abstract

Optimization algorithms were developed for use with the Adaptive Joint Time-Frequency (AJFT) algorithm to reduce Inverse Synthetic Aperture Radar (ISAR) image blurring caused by higher-order target motion. A specific optimization was then applied to 3D motion detection. Evolutionary search methods based on the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm were designed to rapidly traverse the solution space in order to find the parameters that would bring the ISAR image into focus in the cross-range. 3D motion detection was achieved by using the AJTF PSO to extract the phases of 3 different point scatterers in the target data and measuring their linearity when compared to an ideal phase for the imaging interval under investigation. The algorithms were tested against both simulated and real ISAR data sets.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2005
Accession Number
ADA435580

Entities

People

  • Wade Brinkman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • California
  • Coordinate Systems
  • Data Sets
  • Detection
  • Electrical Engineering
  • Experimental Data
  • Genetic Algorithms
  • Mathematical Models
  • Optimization
  • Particle Swarm Optimization
  • Power Spectra
  • Radar Signals
  • Random Variables
  • Signal Processing
  • Two Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology
  • Biotechnology - Cancer Biotech
  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers