基于改进正交匹配追踪算法的压缩感知雷达成像方法  

Compressed Sensing Radar Imaging Methods Based on Modified Orthogonal Matching Pursuit Algorithms

作　　者：刘记红[1] 黎湘[1] 徐少坤[1] 庄钊文[1] 

机构地区：[1]国防科技大学空间电子信息技术研究所,长沙410073

出　　处：《电子与信息学报》2012年第6期1344-1350,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金委杰出青年基金(61025006);国家自然科学基金(61171133)资助课题

摘　　要：运算复杂度高是基于压缩感知(CS)的雷达成像方法走向实用亟待克服的难题。该文利用雷达目标散射率分布的稀疏性,研究了基于改进正交匹配追踪(OMP)算法的2维联合压缩成像方法。首先建立了步进频雷达回波的稀疏表示模型,根据稀疏字典和压缩测量的2维可分离特性,提出一种改进的OMP算法用于雷达图像形成,大大提高了计算效率,并很容易扩展到其他贪婪类算法中。从理论上对几种CS成像算法的性能及资源需求进行了分析比较,表明所提供的算法相比常规的CS算法在存储量和计算量上均具有显著的优势,仿真及暗室数据实验验证了所提成像算法的有效性。High computational complexity is a problem that radar imaging technique based on Compressed Sensing（CS） must overcome for practical applications.In the light of the sparsity of radar target reflectivity,this paper studies 2D joint compressive imaging methods based on modified Orthogonal Matching Pursuit（OMP） algorithms.The sparse representation model of stepped frequency radar echo is established and analyzed,according to the 2D separability of sparse dictionary and compressive measurement,an improved OMP algorithm is proposed for radar image formation,which improves the computational efficiency greatly and can be extended to other greedy algorithms easily.Theoretical comparison and analysis indicate that the proposed methods possess prominent superiority over storage and computation compared to conventional CS algorithms,experiments from both simulated data and measured data verify their validity.

关 键 词：雷达成像 压缩感知 2维可分离 正交匹配追踪(OMP) 快速重构 

分 类 号：TN957.52[电子电信—信号与信息处理]