Multiple Hypothesis Correlation for Space Situational Awareness

Abstract

The primary objective of this program is to perform the necessary basic research to support the development of a statistical, multiple hypothesis tracker (MHT) for space surveillance. Such a MHT framework can serve as the next generation space surveillance system to maintain the space catalog, to identify uncorrelated tracks, and to support conjunction analysis and sensor resource management. Key components in such a system include a consistent characterization of uncertainty, physical modeling, multiple model filtering, and the association problem of determining which tracklets/measurements emanate from which object. To achieve a consistent characterization of uncertainty, Numerica has developed an adaptive Gaussian sum filter which correctly represents and propagates uncertainties and adaptively selects the correct the number of Gaussians in the mixture. Realtime online metrics support the coarsening and refining of the filter to maintain consistent uncertainty.

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Document Details

Document Type
Technical Report
Publication Date
Aug 29, 2011
Accession Number
ADA563914

Entities

People

  • Aubrey B. Poore
  • Joshua T. Horwood

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Bayesian Networks
  • Computational Science
  • Detection
  • Detectors
  • Image Restoration
  • Kalman Filters
  • Low Earth Orbits
  • Mathematical Filters
  • Monte Carlo Method
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Probability
  • Space Objects
  • Space Situational Awareness
  • Space Surveillance
  • Two Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Space Objects