电讯技术2017，Vol.57Issue(1)：53-58,6.DOI:10.3969/j.issn.1001-893x.2017.01.009
基于多测量向量模型的极化探地雷达成像算法
An Imaging Algorithm Based on Multiple Measurement Vectors Model for Polarimetric Ground Penetrating Radar
摘要
Abstract
By exploiting the joint sparsity of the target image space, a novel imaging algorithm based on multiple measurement vectors( MMV) model for polarimetric ground penetrating radar( GPR) is proposed. With the established polarimetric signal model of targets echoes,the multiple polarimetric channel measure-ment data can be treated as the measurement vectors by exploiting the joint sparsity between different polar-imetric channel signals. Then the measurement data is jointly processed by the multi-task Bayesian com-pressive sensing( MT-BCS) algorithm to reconstruct the image of the investigated scene. The processing re-sults of simulation data generated by finite-difference time-domain ( FDTD ) method have demonstrated that the proposed imaging method is superior to the traditional single measurement vector( SMV) based im-aging method both on the accuracy of target location and the suppression of clutter.关键词
极化探地雷达/目标成像/多测量向量/多任务贝叶斯压缩感知Key words
polarimetric ground penetrating radar ( GPR )/target imaging/multiple measurement vectors ( MMV)/multi-task Bayesian compressive sensing( MT-BCS)分类
信息技术与安全科学引用本文复制引用
屈乐乐,桂客,张丽丽..基于多测量向量模型的极化探地雷达成像算法[J].电讯技术,2017,57(1):53-58,6.基金项目
国家自然科学基金资助项目(61671310,61302172) （61671310,61302172）
辽宁省自然科学基金资助项目(2014024002,201602565) （2014024002,201602565）
航空科学基金资助项目(2016ZC54013) （2016ZC54013）
