频域空域二维稀疏SIMO高分辨雷达成像方法

利用频域稀疏的线性调频步进信号(FSCS)作为雷达发射信号,并结合空域稀疏的SIMO雷达阵列来构建二维稀疏的高分辨雷达成像模型。针对该稀疏模型,首先通过对低维数据简单补零处理,然后利用图像熵准则完成对运动目标速度的有效估计。在此基础上,结合压缩感知理论,构造有效的观测矩阵、稀疏变换矩阵以及重构算法,获得目标高分辨距离像(HRRP),进一步提出基于保相性的频域空域二维稀疏SIMO高分辨雷达成像方法。该方法可以大幅减少FSCS脉冲串的子脉冲个数,大幅减少SIMO高分辨雷达接收天线阵元个数,并获得高质量的HRRP和目标二维像。仿真实验验证了本文方法的有效性和鲁棒性。

Two Dimension Sparsity Imaging Method in Frequency and Space Domains for SIMO High-Resolution Radar

Combined with sparse SIMO radar array in space domain,the two dimensional sparsity model for radar imaging with high resolution is established in this paper with frequency-stepped chirp signal(FSCS).First,a velocity estimation method for moving targets is introduced for this model based on image entropy criteria,and the accurate velocity estimation is implemented by simple zero-padding for low dimensional data.Second,in combination of the Compressed Sensing(CS) theory,the effective measurement matrix,the sparsity transform matrix and the reconstruction algorithm are designed to obtain the high-resolution range profile(HRRP),then a phase remain character based new imaging method is proposed for SIMO high-resolution sparse radar by two dimensional sparsity processing in the frequency and the space domains.The model can reduce not only the number of sub-pulses in FSCS burst,but also reduce the number of receivers of SIMO high-resolution radar,in the meanwhile,the high quality HRRP and two dimensional images of targets can be achieved.Effectiveness and robustness of the method are proved by the simulation results.