Abstract
Downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain 3-D scene properties and has broad application prospects. However, the reconstruction of cross-track dimension usually suffers from incomplete observation, which is caused by the non-uniformly and sparsely distributed virtual antenna phase centers. By formulating the cross-track reconstruction into the problem of sparse signal recovery, we introduce two kinds of gridless sparse recovery (GL-SR) methods to DLSLA 3-D SAR cross-track imaging, i.e., atomic norm minimization (ANM) and gridless SPICE (GLS). Compared with the conventional grid-based sparse recovery (GB-SR) methods, which assume that the scatterers are exactly on the discretized grids, the GL-SR methods can avoid the off-grid effect. Experiments compare the performance of GB-SR and GL-SR methods for DLSLA 3-D SAR cross-track reconstruction.
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