A Parametric Detection Approach Using Multichannel Processes

Abstract
This report considers the binary multichannel detection problem for an unknown random signal vector in additive nonwhite interference plus white Gaussian noise. A generalized likelihood ratio is derived based on the vector error residuals from multichannel prediction error filters designed as minimum mean squared error estiamtes under each hypothesis. The observation processes are considered to have an arbitrary in time and across channels. The report outlines a research investigation currently in progress. Keywords: Parametric detection; Multichannel detection; Parameter estimation; Adaptive filtering; Generalized likelihood ratio; Prediction error filtering;

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