基于稀疏孔径的联合稀疏约束干涉ISAR机动目标三维成像

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

In ISAR系统能够实现对目标的3维几何估计,更加有利于目标的分类和识别。同时多功能ISAR/In ISAR系统针对的多是机动性很强的目标,在某些情况下对单个目标仅能获取稀疏孔径观测,尤其是在目标存在机动特性的情况下,更是增加了ISAR成像的难度,这些对传统的ISAR成像算法提出了挑战。为了解决上述这些问题,该文针对机动目标提出一种基于稀疏孔径的联合稀疏约束In ISAR 3维成像方法。对匀加速转动的目标,回波的多普勒调制可以建模成线性调频的形式,并用chirp-傅里叶字典来表征其机动性。接着将联合的多通道In ISAR 2维成像转化为联合稀疏约束的最优化求解问题,并用改进的OMP算法进行求解。然后利用各个通道估计的ISAR图像和调频参数实现对目标的3维几何重构。相比于单通道独立成像,联合多通道稀疏约束成像能获得更好的2维和3维成像结果。最后,进行实测数据实验以验证该文算法的有效性。

Interferometric Inverse SAR（In ISAR） is capable of acquiring three-dimensional image of the moving targets, which is much helpful to the target classification and identification. Meanwhile, multifunctional ISAR/In ISAR 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 In ISAR 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 In ISAR 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.