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International Journal of Antennas and Propagation
Volume 2014, Article ID 196507, 14 pages
http://dx.doi.org/10.1155/2014/196507
Research Article

Knowledge-Aided STAP Using Low Rank and Geometry Properties

1Research Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, China
2Communications Research Group, Department of Electronics, University of York, York YO10 5DD, UK

Received 27 April 2014; Accepted 17 July 2014; Published 12 August 2014

Academic Editor: Hang Hu

Copyright © 2014 Zhaocheng Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.