基于MAPC-RISR的MIMO雷达距离——角度二维超分辨率成像算法  

High-resolution MIMO radar range-angle 2D imaging algorithm based on MAPC-RISR

作　　者：王伟[1] 马跃华[1,2] 郝燕玲[1] 

机构地区：[1]哈尔滨工程大学自动化学院,哈尔滨150001 [2]上海机电工程研究所,上海201109

出　　处：《中国科学：信息科学》2015年第3期372-384,共13页Scientia Sinica(Informationis)

基　　金：教育部新世纪优秀人才计划(批准号:NCET-11-0287);中央高校基本业务费专项资金(批准号:HEUCFX41308);中国博士后科学基金(批准号:2014M550182);黑龙江省博士后特别资助(批准号:LBH-TZ0410);哈尔滨市科技创新人才专项资助(批准号:2013RFXXJ016)资助项目

摘　　要：MIMO雷达作为一种新型的雷达体制,其成像兼具实时性和高分辨率的特点,为了充分发挥MIMO雷达在成像方面的优势,提出一种高分辨率的MIMO雷达成像算法.首先将MIMO雷达成像过程分为距离向脉冲压缩和方位向聚焦成像两个过程,采用多波形自适应脉冲压缩技术(MAPC)实现距离向脉冲压缩和发射波形分离,然后在MIMO雷达虚拟阵列端利用超分辨率空间谱估计方法(RISR)进行方位向聚焦成像,得到了观测区域的距离—角度二维高分辨率的成像结果.理论分析表明,与已有的MIMO雷达自适应成像算法相比,所提方法降低了算法复杂度,提高了运算效率.仿真实验验证了所提MIMO雷达成像算法的有效性与优越性.The relatively new radar architecture, multiple input multiple output（MIMO） radar, has both realtime and high-resolution characteristics. In order to fully expound on the advantages of MIMO radar imaging, a new high-resolution MIMO radar imaging algorithm is presented. The MIMO radar imaging process is divided into two steps： pulse compression in the range direction and azimuth focus. Multi-waveform adaptive pulse compression（MAPC） is used to achieve pulse compression and transmitting waveforms separation; and then, at the end of the MIMO radar virtual array, the re-iterative super-resolution（RISR） spatial spectrum estimation method is utilized to realize azimuth focus. Finally, high-resolution range-angle imaging of the observed area is obtained. Theoretical analysis shows that, compared with the existing adaptive MIMO radar imaging algorithm,the proposed method reduces computational complexity and improves operational efficiency. The results of simulations conducted demonstrate that the proposed method is effective and superior to conventional methods.

关 键 词：MIMO雷达 雷达成像 自适应脉冲压缩 超分辨率角度估计 迭代自适应 

分 类 号：TN957.52[电子电信—信号与信息处理]