Fast ℓ1-regularized space-Time adaptive processing using alternating direction method of multipliers

Journal article (2017)

Authors

Lilong Qin National University of Defense Technology
Manqing Wu China Electronics Technology Group Corporation
X. Wang Microwave Sensing, Signals & Systems - EEMCS
Zhen Dong National University of Defense Technology
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
Copyright: © 2017 Lilong Qin, Manqing Wu, X. Wang, Zhen Dong
DOI: https://doi.org/10.1117/1.JRS.11.026004
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Published Date

2017

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

Abstract

Motivated by the sparsity of filter coefficients in full-dimension space-Time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-To-clutter-noise ratio performance than other algorithms.

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