DocumentCode
498328
Title
Parameters Estimation Method for STAR Based on Clutter Degree of Freedom
Author
Duan Ke-qing ; Fei, Gao ; Wang Yong-liang ; Xie Wen-chong
Author_Institution
Sch. of Electron. Sci. & Eng., NUDT, Changsha, China
Volume
3
fYear
2009
fDate
19-21 May 2009
Firstpage
211
Lastpage
215
Abstract
Space-time autoregression (STAR) is a parametric clutter suppression method based on AR model. The basic theory for clutter suppression of STAR is firstly analyzed. Then a simple and fast parameter estimation method for AR model order based on clutter degree of freedom (DOF) is presented according to the theory of subspace clutter cancellation. The simulation results demonstrate its effectiveness.
Keywords
airborne radar; autoregressive processes; clutter; parameter estimation; space-time adaptive processing; AR model; STAR; airborne radar system; parameter estimation method; parametric clutter suppression method; space-time autoregression method; subspace clutter cancellation; Adaptive filters; Data models; Equations; Intelligent systems; Interference; Matched filters; Parameter estimation; Radar clutter; Spaceborne radar; Training data; DOF; STAP; STAR; clutter suppression;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location
Xiamen
Print_ISBN
978-0-7695-3571-5
Type
conf
DOI
10.1109/GCIS.2009.378
Filename
5209173
Link To Document