Sparse Array Synthesis of Complex Antenna Elements
Arrays of antennas can significantly improve the performances and extend the capabilities of single-element antennas. However, antenna arrays are expensive solutions and therefore it is critical to keep the costs to a minimum. Aperiodic arrays can minimize the number of elements and thus the costs, however their design is far more challenging than uniform arrays, for which well-known, closed-form solutions are available.
Stochastic global optimization techniques can employ complex antenna models and specifications but suffer from high computational complexity. Analytical methods, on the other hand, can handle any problem size but they are limited to simplified models and specifications.
In this thesis we propose a new deterministic method for the design of large aperiodic sparse arrays of realistic and complex antennas. The method is based on the Compressive Sensing theory which has been extended to account for EM phenomena and complex specifications.
In the first part, the hybridization of the method with the full-wave analysis is discussed. Starting from the design in the absence of mutual coupling the array is iteratively refined through an EM analysis until convergence is reached. Results for a linear array of dipoles show the successful correction for the strong coupling degradation which turns out to give rise to a reduction in the number of elements as well. For a planar array of horn antennas the effects are less pronounced but still important in the cross polar levels.
In the second part the method is extended to multi-beam optimization. The array is designed for phase scanning applications when deformations due to phase shifter quantization and mutual coupling effects are considered. Results show that the method accurately synthesizes multi-spot beamforming arrays, although an increase in the number of elements is observed.
Finally, the effects of layout and excitation symmetries have been investigated as a means to reduce the array manufacturing cost. It is shown that, by enforcing a symmetry, the design can be simplified at the expense of an increase in the number of antenna elements.
array signal processing
maximally sparse array
room EB, floor 4, Hörsalsvägen 11
Opponent: Associate Professor Giacomo Oliveri, ELEDIA Research Center, Department of Information Engineering and Computer Science, University of Trento