The Cauchy-Schwarz Divergence for Assessing Situational Information Gain

Abstract

In this paper, we consider the evaluation of information divergence and information gain as they apply to a hybrid random variable (i.e. a random variable which has both discrete and continuous elements) for multi-target tracking problems. In particular, we develop a closed-form solution for the Cauchy- Schwarz information divergence under the assumption that the continuous element of the random variable may be represented by a Gaussian mixture distribution and present the associated relationships for evaluating the Cauchy-Schwarz information gain. The developed information gain relationships are applied to a 0-1 target tracking problem common to space object tracking to determine the sensitivities to the information gain due to probability of detection, prior probability of object existence and measurement noise.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2012
Accession Number
ADA617548

Entities

People

  • Islam I. Hussein
  • Kyle. J. Demars
  • Moriba K. Jah
  • R. S. Erwin

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Satellites
  • Detection
  • Detectors
  • Distribution Functions
  • False Alarms
  • Gaussian Distributions
  • Geometry
  • Measurement
  • Military Research
  • Multitarget Tracking
  • Probability
  • Random Variables
  • Space Objects
  • Space Situational Awareness
  • Target Tracking

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.

Technology Areas

  • Space
  • Space - Space Objects