Accession Number:

ADA175707

Title:

Transmitter Identification with a Small Number of Independent Observers

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1986-09-01

Pagination or Media Count:

143.0

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.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE