ISAR imaging based on sparse chaotic sequence measurement matrices

The construction of measurement matrices is one of the core tasks in compressed sensing inverse synthetic aperture radar (ISAR) imaging. The chaotic sequence measurement matrices are of excellent pseudo-randomness, 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 elements, 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 direction 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.