Combining Imaging and Non-Imaging Observations for Improved Space-Object Identification

Abstract

The accomplishments may be subdivided according to the project s theoretical, experimental, and post-processing/computational objectives. Among the theoretical accomplishments, we list a new model for a sparse representation of man-made space objects and its use, via a new spectral-correlation approach, to segment their material components; the use of 2D segment-boundary data for multiple poses of a man-made space object to recover its 3D shape; new fundamental results involving statistical information and Bayesian error bounds for characterizing the performance of reconstruction algorithms, and feature extraction and estimation fidelity; and the use of Fisher information and the associated Cramer-Rao lower bound on estimator variance to characterize the value of a prior knowledge of object support for spatial-bandwidth extension beyond diffraction-limited observations.

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Document Details

Document Type
Technical Report
Publication Date
Sep 27, 2011
Accession Number
ADA563702

Entities

People

  • David Brady
  • Robert Plemmons
  • Sudhakar Prasad

Organizations

  • University of New Mexico

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Satellites
  • Compressed Sensing
  • Computational Science
  • Data Analysis
  • Data Sets
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Estimators
  • Information Theory
  • Numerical Analysis
  • Optical Detection
  • Quantum Efficiency
  • Space Objects
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Vision.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space
  • Space - Space Objects