Synthesis of Maximally Sparse Arrays Using Compressive Sensing and Full-Wave Analysis for Global Earth Coverage Applications
Journal article, 2016

Global optimization methods can be employed to design aperiodic array antennas that accurately account for their electromagnetic (EM) behavior and complex performance specifications. However, they are computationally expensive and, therefore, limited to small to midsized array problems. On the other hand, analytical methods do not suffer from this problem, but often assume idealized antenna elements and fully adjustable excitation controls, thereby excluding beam degradation effects caused, e.g., by mutual coupling (MC) and quantized phase shifters. We present a fast design method for large maximally sparse arrays that is capable of handling the aforementioned limitations. It is based on the previously published combined EM-Compressive Sensing approach, which has been herein generalized for multibeam optimization, and where we also exploit array symmetry in order to reduce the design complexity. Results are obtained for a circular array ( 100 λ diameter) of horn antennas operating in a multibeam SATCOM scenario, and demonstrate that even weak MC effects and small phase quantization are important when very demanding sidelobe and cross-polarization levels are required.

sparse array antennas

satellite applications

Multibeam antennas

Author

Carlo Bencivenni

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Marianna Ivashina

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Rob Maaskant

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Johan Wettergren

Ruag Space AB

IEEE Transactions on Antennas and Propagation

0018926x (ISSN) 15582221 (eISSN)

Vol. 64 11 4872-4877 7524015

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/TAP.2016.2594840

More information

Latest update

9/6/2018 1