Title :
A unified framework for space-time adaptive processing
Author :
Rangaswamy, Muralidhar
Author_Institution :
Arcon Corp., Waltham, MA, USA
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;
Conference_Titel :
Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on
Conference_Location :
Portland, OR
Print_ISBN :
0-7803-5010-3
DOI :
10.1109/SSAP.1998.739409
