基于混沌序列稀疏化测量矩阵的ISAR成像

ISAR Imaging Based on Sparse Chaotic Sequence Measurement Matrices

在压缩感知逆合成孔径雷达(ISAR)成像中,构造测量矩阵是核心工作之一.混沌序列测量矩阵具有良好的伪随机性,能满足压缩测量的要求.针对混沌序列测量矩阵中非零随机元数目多而造成硬件实现困难的问题,文中提出了一种混沌序列稀疏化测量矩阵的构造方法.首先对混沌序列测量矩阵进行优化,然后沿矩阵对角方向进行置零稀疏化,最后将其应用于微波暗室进行ISAR成像实验.结果表明,与传统高斯随机矩阵成像方法相比,文中方法在降低计算复杂度、硬件实现难度基础上达到了ISAR成像的准确聚焦.

The construction of measurement matrices is one of the core tasks in compressed sensing inverse synthe-tic aperture radar ( ISAR) imaging.The chaotic sequence measurement matrices are of excellent pseudo-random-ness, which can meet the requirements of compressive measurement.As it is difficult to implement the hardware engineering of the chaotic sequence measurement matrices because of the huge number of independent random ele-ments, a construction method of sparse chaotic sequence measurement matrices is proposed in this paper.In the method, the chaotic sequence measurement matrices are optimized, and then setting the zero along the diagonal di-rection is performed to make the matrix sparse.Finally, the sparse chaotic sequence measurement matrices are used to conduct ISAR imaging experiments in a microwave anechoic chamber.The results show that, in comparison with the Gauss random matrix imaging method, the proposed method achieves an accurate focusing of ISAR imaging and reduces the computational complexity and the hardware implementation difficulty.