Title :
Compressive Sensing Pattern Matching Techniques for Synthesizing Planar Sparse Arrays
Author :
Viani, F. ; Oliveri, G. ; Massa, A.
Author_Institution :
ELEDIA Res. Center, Univ. of Trento, Trento, Italy
Abstract :
In this paper, the design of sparse planar arrays is yielded through a set of innovative and efficient pattern matching algorithms within the Bayesian Compressive Sensing (BCS) framework. Towards this end, the 2D sparse synthesis problem is formulated in a probabilistic fashion and the single-task (ST) and the multi-task (MT) BCS solutions are derived. The results from a numerical validation concerned with different aperture size and target patterns prove that the proposed implementations enable an element saving ranging from 25% up to 87%, while achieving a reliable beam control.
Keywords :
array signal processing; compressed sensing; 2D sparse synthesis problem; BCS framework; Bayesian compressive sensing framework; aperture size; beam control; compressive sensing pattern matching technique; multitask BCS solution; planar sparse array synthesis; probabilistic fashion; single-task BCS solution; sparse planar array design; Array synthesis; Bayesian compressive sampling (BCS); complex-weight pattern; contoured beams; planar arrays; sparse arrays;
Journal_Title :
Antennas and Propagation, IEEE Transactions on
DOI :
10.1109/TAP.2013.2267195
