Estimating the number of signals in presence of colored noise

Pinyuen Chen, Gerard J. Genello, Michael C. Wicks

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Number of pages6
StatePublished - 2004
EventProceedings of the IEEE Radar Conference - Philadelphia, PA, United States
Duration: Apr 26 2004Apr 29 2004


OtherProceedings of the IEEE Radar Conference
Country/TerritoryUnited States
CityPhiladelphia, PA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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