Multiple Model Adaptive Estimation for Space-Time Point Process Observations.

Abstract

The problem addressed by this research is one of estimating parameters of an underlying stochastic process from observations of a point process where the point process is dependent on the underlying process and the observations are corrupted by point process noise. A second, closely related problem is that of allowing feedback control for a system in which observations of a point process signal are corrupted by point process noise. This will provide a method for investignating the optimal stochastic adaptive controller for the system. The major contribution of this research is a method for developing an estimator for the above mentioned point process signal in point process noise environment. The method allows feedback to the model from the observations thus providing a means for control. This method is used to develop the estimator for the neutral particle beam pointing and tracking problem which motivated this research. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1982
Accession Number
ADA124827

Entities

People

  • David E. Meer

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Data Science
  • Decision Theory
  • Detectors
  • Engineering
  • Equations
  • Estimators
  • Information Science
  • Mathematical Filters
  • Neutral Particle Beams
  • Particle Beams
  • Probability
  • Random Variables
  • Stochastic Processes
  • Two Dimensional

Readers

  • Robotics and Automation.
  • Statistical inference.
  • Theoretical Analysis.

Technology Areas

  • Directed Energy
  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers