A Greedy Approach for Sparse Angular Aperture Radar

Abstract

We present a novel algorithm for radar imaging of point scatterers using a sparse number of spatially separated sensors. Such sparse sensing scenarios are prototypical of many applications wherein a limited number of sensors are distributed over a geographical area; or where environmental and/or systemic constraints enforce a sparse sampling of angular aperture. Our underlying assumption is that the image is sparse with respect to the Gabor basis set. We then introduce the concept of an orbit-viz. the locus of all projections made by a spatial basis-and formulate the radar imaging problem as that of sparsifying the number of orbits that comprise the radon measurements of the source. We demonstrate how our algorithm outperforms FFT-based and Compressive-sensing based reconstruction algorithms for point-scatterer images describe relevant theoretical performance bounds of our algorithm, and point to future research arising from this work.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2010
Accession Number
ADA538754

Entities

People

  • Raghu G. Raj
  • Ronald Lipps
  • Victor C. Chen

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude
  • Aspect Angle
  • Compressed Sensing
  • Computational Complexity
  • Construction
  • Detectors
  • Dictionaries
  • Equations
  • Flexible Structures
  • Frequency
  • Geometry
  • Image Processing
  • Image Reconstruction
  • Measurement
  • Radar Imaging
  • Time Domain

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.
  • Radar Systems Engineering.

Technology Areas

  • Space
  • Space - Space Objects