Skip to Main content Skip to Navigation
Journal articles

Detection of Gaussian Signal Using Adaptively Whitened Data

Abstract : The adaptive matched filter, like many other adaptive detection schemes, uses in its test statistic the data under test whitened by the sample covariance matrix S of the training samples. Actually, it is a generalized likelihood ratio test (GLRT) based on the conditional (i.e., for given S) distribution of the adaptively whitened data. In this letter, we investigate detection of a Gaussian rank-one signal using the marginal (unconditional) distribution of the adaptively whitened data. A first contribution is to derive the latter and to show that it only depends on a scalar parameter, namely the signal to noise ratio. Then, a GLRT is formulated from this unconditional distribution and shown to have the constant false alarm rate property. We show that it bears close resemblance with the plain GLRT based on the whole data set (data under test and training samples). The new detector performs as well as the plain GLRT and even better with multiple cells under test and low training sample support.
Document type :
Journal articles
Complete list of metadata

Cited literature [25 references]  Display  Hide  Download
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Monday, May 25, 2020 - 2:42:58 PM
Last modification on : Tuesday, May 26, 2020 - 8:52:46 AM


Files produced by the author(s)



Olivier Besson. Detection of Gaussian Signal Using Adaptively Whitened Data. IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2019, 26 (3), pp.430-434. ⟨10.1109/LSP.2019.2893761⟩. ⟨hal-02618454⟩



Record views


Files downloads