DocumentCode :
2811169
Title :
Knowledge-aided STAP algorithm using convex combination of inverse covariance matrices for heterogenous clutter
Author :
Fa, Rui ; De Lamare, Rodrigo C. ; Nascimento, Vítor H.
Author_Institution :
Dept. of Electron., Univ. of York, York, UK
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
2742
Lastpage :
2745
Abstract :
Knowledge-aided space-time adaptive processing (KA-STAP) algorithms, which incorporate a priori knowledge into radar signal processing methods, have the potential to substantially enhance detection performance while combating heterogeneous clutter effects. In this paper, we develop a KA-STAP algorithm to estimate the inverse interference covariance matrix rather than the covariance matrix itself, by combining the inverse of the covariance known a priori, R0-1, and the inverse sample covariance matrix estimate R̂-1. The computational load is greatly reduced due to the avoidance of the matrix inversion operation. We also develop a cost-effective algorithm based on the minimum variance (MV) criterion for computing the mixing parameter that performs a convex combination of R0-1 and R̂-1. Simulations show the potential of our proposed algorithm, which obtain substantial performance improvements over prior art.
Keywords :
airborne radar; covariance matrices; radar clutter; radar signal processing; space-time adaptive processing; KA-STAP algorithm; airborne radar applications; heterogenous clutter; inverse interference covariance matrix; knowledge-aided space-time adaptive processing algorithms; minimum variance criterion; radar signal processing methods; Airborne radar; Clutter; Computational modeling; Covariance matrix; Doppler radar; Interference; Radar antennas; Radar detection; Signal processing algorithms; Signal to noise ratio; Space-time adaptive processing; airborne radar applications; knowledge-aided techniques;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5496217
Filename :
5496217
Link To Document :
بازگشت