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Knowledge-Aided STAP Using Low Rank and Geometry Properties
by
Zhaocheng Yang
,
Rodrigo C De Lamare
,
Xiang Li
,
Hongqiang Wang
BibTeX
@MISC{Yang_knowledge-aidedstap,
author = {Zhaocheng Yang and Rodrigo C De Lamare and Xiang Li and Hongqiang Wang},
title = {Knowledge-Aided STAP Using Low Rank and Geometry Properties},
year = {}
}
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Abstract
This paper presents knowledge-aided space-time adaptive processing (KA-STAP) algorithms that exploit the low-rank dominant clutter and the array geometry properties (LRGP) for airborne radar applications. The core idea is to exploit the clutter subspace that is only determined by the space-time steering vectors, by employing the Gram-Schmidt orthogonalization approach to compute the clutter subspace. Simulation results illustrate the effectiveness of our proposed algorithms.
