A new method of partially adaptive constant false-alarm rate (CFAR) detection is introduced. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The performance is evaluated using the general framework of space-time adaptive processing (STAP) for the cases of both known and unknown covariance. It is demonstrated that this new approach to partially adaptive STAP outperforms the more complex eigen-analysis approaches using both simulated DARPA Mountain Top data and true pulse-Doppler radar data collected by the MCARM radar.
Multistage partially adaptive STAP CFAR detection algorithm
IEEE Transactions on Aerospace and Electronic Systems ; 35 , 2 ; 645-661
01.04.1999
2447360 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
PAPERS - Multistage Partially Adaptive STAP CFAR Detection Algorithm
Online Contents | 1999
|CFAR detection and estimation for STAP radar
IEEE | 1998
|CFAR Detection and Estimation for STAP Radar
Online Contents | 1998
|Partially Adaptive STAP using the FRACTA Algorithm
Online Contents | 2009
|Partially Adaptive STAP using the FRACTA Algorithm
IEEE | 2009
|