Geometric Invariants for Radar Motion Estimation

Abstract

We describe an algorithm for reconstructing the motion of a radar platform relative to a scene, given video phase history and an estimate of the sensor's average speed and altitude. This algorithm is a more robust alternative to previous geometric-invariant-based approaches, capable of producing motion estimates accurate enough for the formation of back projection imagery. The algorithm is modular; in the first phase, the algorithm estimates the range to fixed locations in the scene as a function of time. In the second phase, these range tracks are used by a specialized solver to recover the relative positions of the tracked locations in the scene, along with the relative position of the sensor platform as a function of time. We demonstrate the effectiveness of the algorithm by forming an image from the large-scene Gotcha dataset, without the use of GPS or inertial measurement unit data. The results are compared to those from another invariant-based algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Jan 04, 2021
Accession Number
AD1120548

Entities

People

  • Matthew Ferrara

Organizations

  • Matrix Research (United States)

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Applied Mathematics
  • Coordinate Systems
  • Curvature
  • Data Sets
  • Detectors
  • Differential Equations
  • Equations
  • Far Field
  • Frequency
  • Geometric Forms
  • Geometry
  • Global Positioning Systems
  • Images
  • Military Research
  • Moving Targets
  • New York
  • Radar
  • Relative Motion
  • Scattering
  • Scientific Research
  • Synthetic Aperture Radar
  • Three Dimensional
  • Two Dimensional
  • United States

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Inertial Navigation Systems.

Technology Areas

  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers