Sparse solution methods for inverse problems in antennas and propagation

This paper reviews recent advances of sparse solution methods for solving inverse problems in antennas and propagation. Mathematical formulation of sparse solution methods is first presented. Typical applications are then introduced, including direction of arrival estimation, extrapolation of electromagnetic signals, array diagnosis, and array beamforming. It is shown that, by utilizing the a priori knowledge of sparseness, sparse solution methods outperform conventional methods. After reviewing recent progress, future trends are finally discussed.