基于单快拍稀疏重构的阵列雷达前视成像  

Forward-looking Imaging for Array Radar Based on Single Snapshot Sparse Reconstruction

作　　者：赵会宁[1] 贺思三[1] 樊晨阳 杜敦伟 ZHAO Huining;HE Sisan;FAN Chenyang;DU Dunwei(Air and Missile Defense College,Air Force Engineering University,Xi'an 710051,China;Beijing Institute of Mechanical and Electrical Engineering,Beijing 100074,China)

机构地区：[1]空军工程大学防空反导学院,西安710051 [2]北京机电研究所,北京100074

出　　处：《现代雷达》2022年第2期23-28,共6页Modern Radar

摘　　要：针对阵列雷达前视高分辨成像问题,文中提出了一种基于单快拍数据稀疏重构的成像算法。在对各阵元回波信号进行脉冲压缩及运动校正后,以波束指向角为中心在主瓣范围内构建信号矢量及对应观测矩阵,利用稀疏贝叶斯学习算法对当前指向角多个阵元的单快拍数据进行稀疏重构,得到散射系数分布;进一步对不同指向角重构所得散射系数进行幅度积累,得到最终的前视图像。仿真结果表明,该算法能在低角度采样率条件下获得有效的前视超分辨图像。To improve the azimuth angle resolution for array radar forward-looking imaging,an algorithm based on single snapshot sparse reconstruction is proposed.After pulse compression and geometric correction for each array element signals,the observation matrix is constructed within the main lobe angle,and the scattering coefficient distribution at current pointing angle is obtained by sparse Bayesian learning for the sparse reconstruction of single snapshot data.Further,the final forward-looking image is obtained by calculating the scattering coefficients at different pointing angles.Simulation results show that the algorithm can obtain focused forward-looking images under low-angle sampling rate.

关 键 词：前视成像 压缩感知 阵列雷达 稀疏贝叶斯学习算法 

分 类 号：TN957[电子电信—信号与信息处理]