Innovations based detection algorithm for correlated non-Gaussian random processes

M Rangaswamy,J.H Michels,D.D Weiner

doi:10.1109/ssap.1992.246858

Innovations based detection algorithm for correlated non-Gaussian random processes

M Rangaswamy, J.H Michels + Show 1 more

https://doi.org/10.1109/ssap.1992.246858

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Publication Date: Oct 7, 1992

Citations: 4

Affiliation: Syracuse University, Advanced Scientific Concepts (United States)

#Spherically Invariant Random Processes #Probability Density Function + Show 8 more

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Abstract

This paper addresses the problem of detecting a known signal in additive correlated nonGaussian noise using the innovations approach. There is no unique specification for the joint probability density function (PDF) of N correlated nonGaussian random variables. The authors overcome this problem by using the theory of spherically invariant random processes (SIRP) and derive the innovations based detectors. The optimal estimators for obtaining the innovations processes are linear and the resulting detector is canonical for the class of PDFs arising from SIRPs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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