A unified framework for space-time adaptive processing

Author

Rangaswamy, Muralidhar

Author_Institution

Arcon Corp., Waltham, MA, USA

fYear

1998

fDate

14-16 Sep 1998

Firstpage

360

Lastpage

363

Abstract

This work provides a common framework for three recently proposed space-time adaptive processing (STAP) methods. A common goal of these methods is to reduce computational complexity and sample support requirements. It is shown that the canonical correlations model provides a mechanism for treating the STAP methods in a unified framework

Keywords

computational complexity; correlation theory; signal sampling; space-time adaptive processing; STAP; canonical correlations model; computational complexity; sample support; space-time adaptive processing; Adaptive arrays; Clutter; Computational complexity; Covariance matrix; Interference; Matched filters; Maximum likelihood estimation; Signal processing; Testing; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on

Conference_Location

Portland, OR

Print_ISBN

0-7803-5010-3

Type

conf

DOI

10.1109/SSAP.1998.739409

Filename

739409

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2469749