摘要
针对相关干涉仪测向系统,提出了一种基于压缩感知的测向算法.该算法将相关干涉仪的测量矢量分解为以测向数据库为基底的含有噪声的稀疏表示,采用再加权的l1范数凸优化算法,迭代更新加权矢量,以逼近最优的l0范数.所提算法和传统的计算相关系数最大值方法相比,额外利用了辐射源信号在空域上的稀疏性,可以对同频多信号进行测向.采用计算机仿真对所提算法的性能进行了验证.
An algorithm based on compressive sensing is proposed for direction finding with correlative interferometry.It decomposes the measurement vector of a correlative interferometer into a noise-contaminated sparse representation with respect to the database,and performs reweighted l 1-norm optimization to approximate the optimal l 0-norm optimization,which updates the weights iteratively.Compared with the conventional method of correlation coefficient maximization,the proposed algorithm accounts for the spatial sparsity of the emitters,which leads to its capability of direction finding of multiple signals of the same frequency.Simulated results have demonstrated the performance of the proposed algorithm.
作者
苟晓鸣
孙中森
唐怀玉
单中尧
李永庆
GOU Xiaoming;SUN Zhongsen;TANG Huaiyu;SHAN Zhongyao;LI Yongqing(China Research Institute of Radiowave Propagation,Qingdao 266107,China)
出处
《电波科学学报》
EI
CSCD
北大核心
2018年第5期532-536,共5页
Chinese Journal of Radio Science
基金
青岛科技专项课题(青科创14-6-1-8-ZDZX)
国家863计划项目(2015AA7124068A)
国家自然科学基金(6133190102)
关键词
测向
相关干涉仪
压缩感知
稀疏性
凸优化
direction finding
correlative interferometry
compressive sensing
sparsity
convex optimization
