Adaptive Sparse ISAR Imaging for Objects With Off-grid Scatterers

Due to the sparsity of inverse synthetic aperture radar (ISAR) images, compressive sensing (CS) has been introduced to ISAR imaging for resolution improvement. However, conventional CS ISAR algorithms assume that target scatterers are on the predefined range-Doppler grid, which will cause performance degradation in practical applications as scatterers are generally off-grid. In this paper, we investigate CS ISAR imaging technique for targets with off-grid scatterers. Based on adaptive grids, a two dimensional sparse ISAR imaging algorithm is presented. Simulation results validate the effectiveness of the proposed algorithm.