Recursive KA-STAP algorithm based on QR decomposition

Author

He Ming Dong ; Cao Jian Shu

Author_Institution

Res. Inst. of Electron. Sci. & Technol., UESTC, Chengdu, China

fYear

2013

fDate

24-25 Oct. 2013

Firstpage

391

Lastpage

394

Abstract

The performance of space-time adaptive processing (STAP) for airborne radar decreases due to the nonstationarity of clutter in heterogeneous clutter environment. To solve this problem, a knowledge-aided space-time adaptive processing (KA-STAP) algorithm based on QR decomposition is proposed in this paper. It is a fast recursive algorithm implemented in the data domain directly without sample matrix inverse (SMI). The simulation results show that the recursive KA-STAP algorithm based on QR decomposition has the same weight vector with the SMI algorithm and better clutter suppression performance compared with traditional STAP.

Keywords

airborne radar; matrix algebra; optimisation; radar clutter; space-time adaptive processing; QR decomposition; SMI; airborne radar; clutter suppression performance; data domain; heterogeneous clutter environment; knowledge-aided space-time adaptive processing; recursive KA-STAP algorithm; sample matrix inverse; weight vector; Adaptation models; Clutter; Computational modeling; Covariance matrices; Matrix decomposition; Simulation; Vectors; QR decomposition; Space-time adaptive processing (STAP); knowledge-aided (KA); nonstationarity; sample matrix inverse (SMI);

fLanguage

English

Publisher

ieee

Conference_Titel

Microwave and Millimeter Wave Circuits and System Technology (MMWCST), 2013 International Workshop on

Conference_Location

Chengdu

Type

conf

DOI

10.1109/MMWCST.2013.6814532

Filename

6814532