Joint Sparsity Constraint Interferometric ISAR Imaging for 3-D Geometry of Maneuvering Targets with Sparse Apertures

Interferometric Inverse SAR (InISAR) is capable of acquiring three-dimensional image of the moving targets, which is much helpful to the target classification and identification. Meanwhile, multifunctional ISAR/InISAR system aims at maneuvering targets and only sparse aperture measurements are available for each target, which is a challenge to the conventional ISAR imaging algorithms. A joint sparsity-constraint InISAR 3-D imaging approaches is presented for maneuvering targets with sparse apertures. For a uniformly accelerated rotation target, the Doppler modulation in echo is formulated as chirp sensing code under a chirp-Fourier dictionary to represent the maneuverability. Then the joint multi-channel InISAR imaging approach is converted into a joint sparse constraint optimization. And a modified Orthogonal Matching Pursuit (OMP) algorithm is employed to solve the optimization. The 3-D target geometry is followed by using obtaining 2-D images and estimated chirp parameters. Finally, the experiment using measured data is performed to confirm the effectiveness of the proposed method.