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
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;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.378
