The problem of adaptively detecting a signal confined to a given vector subspace in interference modeled as a zero-mean complex Gaussian N-vector is considered. The correlation properties of interference are not known but are estimated from a given set of secondary (or reference) vectors. The dimension of the known signal subspace is N/sub s/, where 1/spl les/N/sub s//spl les/N. The Generalized Likelihood Ratio Test (GLRT) is cast in a slightly different setting to show that it belongs to a class of invariant tests. The maximal invariants for the class of invariant tests are identified and the joint probability density function of the maximal invariants under both the null hypothesis H/sub 0/ and the alternate hypothesis H/sub 1/ are derived. These expressions are used to show that for 1/spl les/N/sub s/


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    Title :

    Performance of the GLRT for adaptive vector subspace detection


    Contributors:


    Publication date :

    1996-10-01


    Size :

    1647805 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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