Accession Number:

ADA454910

Title:

On Periodic Pulse Interval Analysis with Outliers and Missing Observations

Descriptive Note:

Research rept.

Corporate Author:

MARYLAND UNIV COLLEGE PARK INST FOR SYSTEMS RESEARCH

Personal Author(s):

Report Date:

1996-01-23

Pagination or Media Count:

32.0

Abstract:

Analysis of periodic pulse trains based on time of arrival is considered, with perhaps very many missing observations and contaminated data. A period estimator is developed based on a modified Euclidean algorithm. This algorithm is a computationally simple, robust method for estimating the greatest common divisor of a noisy contaminated data set. The resulting estimate, while not maximum likelihood, is used as initialization in a three-step algorithm that achieves the Cramer-Rao bound for moderate noise levels, as shown by comparing Monte Carlo results with the Cramer-Rao bounds. An extension using multiple independent data records is also developed that overcomes high levels of contamination.

Subject Categories:

  • Numerical Mathematics
  • Radiofrequency Wave Propagation

Distribution Statement:

APPROVED FOR PUBLIC RELEASE