双基地ISAR稀疏孔径机动目标MTRC补偿成像算法  

Bistatic ISAR sparse aperture maneuvering target MTRC compensation imaging algorithm

作　　者：朱瀚神 胡文华 郭宝锋 焦丽婷 朱晓秀 朱常安 ZHU Hanshen;HU Wenhua;GUO Baofeng;JIAO Liting;ZHU Xiaoxiu;ZHU Chang’an(Department of Electronic and Optical Engineering,Shijiazhuang Campus,Army Engineering University,Shijiazhuang 050003,China;Unit 32398 of the PLA,Beijing 100192,China)

机构地区：[1]陆军工程大学石家庄校区电子与光学工程系,河北石家庄050003 [2]中国人民解放军32398部队,北京100192

出　　处：《系统工程与电子技术》2023年第7期2022-2030,共9页Systems Engineering and Electronics

基　　金：河北省自然科学基金(F2019506031);陆军工程大学基础前沿科技创新项目(KYSZJQZL2020)资助课题。

摘　　要：针对双基地逆合成孔径雷达(bistatic inverse synthetic aperture radar,Bi-ISAR)稀疏孔径条件下机动目标的越距离单元徙动(migration through range cells,MTRC)补偿难的问题,提出了一种将Keystone变换与加权l 1范数稀疏约束最优化算法相结合的补偿并成像的算法。Bi-ISAR稀疏孔径机动目标回波完成平动补偿后,假设目标图像各像元稀疏非同分布,对每个距离单元建立含Keystone变换参数与时变双基地角的变尺度傅里叶变换稀疏基,使用加权l 1范数稀疏约束最优化算法逐距离单元恢复方位向的散射系数并成像。实验结果证明了所提算法的有效性和鲁棒性。Aiming at the problem that it is difficult to compensate the migration through range cells(MTRC)of maneuvering target under the condition of sparse aperture in bistatic inverse synthetic aperture radar(Bi-ISAR)system,a compensated imaging method combining Keystone transform and weighted l 1 norm sparse constrained optimization algorithm is proposed.Based on the Bi-ISAR sparse aperture echo data after translation compensation,assuming that each pixel of the target image is sparse and non identically distributed,a variable scale Fourier transform sparse basis with Keystone transform parameters and time-varying bistatic angle is established for each range cell,and the weighted l 1 norm sparse constrained optimization algorithm is used to recover the azimuth scattering coefficient imaging.Experimental results show the effectiveness and robustness of the proposed algorithm.

关 键 词：双基地逆合成孔径雷达 稀疏孔径 机动目标 越距离单元徙动 

分 类 号：TN957.52[电子电信—信号与信息处理]