Higher-order statistic-based detection of non-Gaussian signals

Using the Gaussian noise rejection property of higher-order spectra (HOS), HOS-based detectors can outperform conventional second-order (SOS) techniques in certain scenarios. In this thesis we study the strengths and limitations of HOS detection techniques, as well as proper applications for them. We first compare existing frequency-domain HOS detection techniques with new tests that we propose. We formulate a new F-test statistic and derive refined conditional distributions for the test proposed by Hinich. We calculate the optimal smoothing bandwidth for the HOS estimate components of our F-test and his test, producing the best detector performance. These new bandwidths yield significant improvements in detector performance over previous results.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Garth, Lee McCandless

Contributors dc:contributor

• Bresler, Yoram

• Statistics
• Engineering, Electronics and Electrical

Statement dc:rights

• Copyright 1996 Garth, Lee McCandless

Language dc:language

eng

Identifier

9780591198188
AAI9712278
(UMI)AAI9712278

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/22898