2004 IEEE Radar Conference

Innovative Radar Technologies - Expanding System Capabilities

 
 
 April 26-29, 2004 Wyndham Philadelphia at Franklin Plaza Philadelphia, Pennsylvania
 
 
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Poster 4.7
Estimating the number of signals in presence of colored noise

Pinyuen Chen - Syracuse University, Gerard J. Genello - Air Force Research Laboratory, Michael C. Wicks - Air Force Research Laboratory

Wed, 28 April 2004, 3:20 PM - 4:10 PM


Abstract

In this paper, statistical ranking and selection theory is used to estimate the number of signals present in colored noise. The data structure follows the well-known MUltiple SIgnal Classification (MUSIC) model. We are dealing with the eigen-analyses of a matrix, using the MUSIC model and colored noise. The data matrix can be written as the product of a covariance matrix and the inverse of second covariance matrix. We propose a multi-step selection procedure to construct a confidence interval on the number of signals present in a data set. Properties of this procedure will be stated and proved. Those properties will be used to compute the required parameters (procedure constants). Numerical examples are given to illustrate our theory.

Bio

Dr. Pinyuen Chen - Syracuse University

Pinyuen Chen received his Ph. D. in statistics at UC Santa Barbara under the guidance of Milton Sobel in 1982. His research area includes statistical ranking and selection, multivariate analysis, and statistical signal processing. He is a Professor and the Director of Interdisciplinary Statistics Program at Syracuse University.

 
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