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Reduced-rank STAP algorithm for adaptive radar based on joint iterative optimization of adaptive filters

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3 Author(s)
Rui Fa ; Dept. of Electron., Univ. of York, York ; de Lamare, R.C. ; Zanatta-Filho, D.

In this paper, we develop a novel reduced-rank space-time adaptive processing (STAP) algorithm based on joint iterative optimization of filters for adaptive radar applications. The proposed algorithm consists of a joint iterative optimization of a bank of full-rank adaptive filters that forms the projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe constrained minimum variance (CMV) expressions for the design of the projection matrix and the reduced-rank filter. Adaptive algorithms including normalized least-mean-squares (NLMS) and recursive least square (RLS) are derived for its efficient implementation. Simulations for a clutter-plus-jamming suppression application show that the proposed STAP algorithm outperforms the state-of-the-art reduced-rank schemes in convergence and tracking at significantly lower complexity.

Published in:

Signals, Systems and Computers, 2008 42nd Asilomar Conference on

Date of Conference:

26-29 Oct. 2008