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Journal of Applied Remote Sensing • Open Access

Fast 1-regularized space-time adaptive processing using alternating direction method of multipliers
Author(s): Lilong Qin; Manqing Wu; Xuan Wang; Zhen Dong

Paper Abstract

Motivated by the sparsity of filter coefficients in full-dimension space-time adaptive processing (STAP) algorithms, this paper proposes a fast 1-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.

Paper Details

Date Published: 12 April 2017
PDF: 13 pages
J. Appl. Rem. Sens. 11(2) 026004 doi: 10.1117/1.JRS.11.026004
Published in: Journal of Applied Remote Sensing Volume 11, Issue 2
Show Author Affiliations
Lilong Qin, National Univ. of Defense Technology (China)
Aalto Univ. (Finland)
Manqing Wu, China Electronics Technology Group Corp. (China)
Xuan Wang, Technische Univ. Delft (The Netherlands)
Zhen Dong, National Univ. of Defense Technology (China)


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