Adaptive Matched Direction Detector

Author

Besson, Olivier ; Scharf, Louis L. ; Kraut, Shawn

Author_Institution

Dept. of Avionics & Syst., ENSICA, Toulouse

fYear

2006

fDate

12-14 July 2006

Firstpage

137

Lastpage

141

Abstract

We consider the problem of detecting a partially unknown signal, in the presence of unknown noise, using multiple snapshots in the primary data. To account for uncertainties about signal´s signature, we assume that the steering vector lies on an unknown line in a known linear subspace. Additionally, we consider a partially homogeneous environment, for which the covariance matrix of the primary and the secondary data have the same structure, but possibly different levels. We study the invariances of the detection problem and derive the maximal invariant. A two-step generalized likelihood ratio test (GLRT) is formulated and compared with a 2-step GLRT which assumes that the steering vector is known

Keywords

adaptive signal detection; covariance matrices; adaptive matched direction detector; covariance matrix; linear subspace; multiple snapshots; partially unknown signal detection; two-step generalized likelihood ratio test; Aerospace electronics; Background noise; Detectors; Laboratories; Radar detection; Statistics; Testing; Uncertainty; Vectors; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Sensor Array and Multichannel Processing, 2006. Fourth IEEE Workshop on

Conference_Location

Waltham, MA

Print_ISBN

1-4244-0308-1

Type

conf

DOI

10.1109/SAM.2006.1706108

Filename

1706108