Adaptive robust constrained matched filter and subspace detection

Author

Desai, Mukund ; Mangoubi, Rami

Author_Institution

C.S. Draper Lab., Cambridge, MA, USA

Volume

1

fYear

2002

fDate

3-6 Nov. 2002

Firstpage

768

Abstract

A minimax methodology for formulating adaptively robust and sensitive matched filter and subspace detectors is provided, where the signal and interference of structured noise are partially known. The signal and interference subspaces are assumed to reside in conical regions of the measurement space, and the gain parameters can have bounded magnitude. It is shown that the minimax approach permits the design of a rich variety of matched filter and subspace detectors that vary in the degree of robustness and sensitivity.

Keywords

adaptive filters; interference (signal); matched filters; minimax techniques; signal detection; CFAR; adaptive robust detector; adaptive robust matched filter; conical regions; constant false alarm rate; interference subspaces; magnitude constraints; minimax methodology; sensitivity; signal subspaces; structured noise; subspace detection; Adaptive signal detection; Detectors; Gaussian noise; Interference constraints; Laboratories; Magnetic resonance imaging; Matched filters; Minimax techniques; Noise robustness; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-7576-9

Type

conf

DOI

10.1109/ACSSC.2002.1197283

Filename

1197283