Transmitter Identification with a Small Number of Independent Observers

Abstract

This thesis presents and compares algorithms that identify a signal (one or two parameters) from a known group. This identification is done with a small number of observes. Using simulation the algorithms are compared for robustness and accuracy. Robustness is simulated by drawing observations from a Cauchy and also from a mixed normal with two different mixing probabilities. The results of the simulations demonstrate that that the maximum likelihood estimators based on the Candy or the mixed normal are satisfactory for both robust and nonrobust (outlier-prone) situations, while classical linear methods perform poorly if outliers are present. Keywords include: Identification, MLE, Transmitter, and Observations.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1986
Accession Number
ADA175707

Entities

People

  • Andrew G. Meldrum

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computers
  • Data Analysis
  • Estimators
  • Identification
  • Measurement
  • Normal Distribution
  • Observation
  • Observers
  • Operations Research
  • Probability
  • Random Variables
  • Schools
  • Simulations
  • Transmitters
  • United States

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Statistical inference.