雷达学报2018，Vol.7Issue(2)：194-201,8.DOI:10.12000/JR16121
频控阵MIMO雷达中基于稀疏迭代的多维信息联合估计方法
Multidimensional Parameter Estimation Method Based on Sparse Iteration in FDA-MIMO Radar
摘要
Abstract
To accurately identify the range of each target, traditional Multiple-Input Multiple-Output (MIMO) radar techniques not only require designing a shift matrix to describe different range bins but also a large number of snapshots. To alleviate this problem, a multidimensional parameter estimation method based on sparse iteration is proposed for a MIMO radar with Frequency Diverse Array (FDA). The FDA-MIMO radar uses small frequency increments across the array elements, and its transmit steering vector is a function of both range and angle. On the basis of the feature of the FDA-MIMO radar, we consider a weighted lq(0<q ≤1) minimization problem that is solved using a sparse iterative algorithm. Finally, the target parameters (the amplitude, range, and angle) are obtained using a single snapshot. Moreover, numerical simulations are used to demonstrate the superior performance of the proposed method compared with those of DAS, IAA, and IAA-R.关键词
MIMO雷达/频控阵/距离估计/参数估计/新体制雷达Key words
Multiple-Input Multiple-Output (MIMO) radar/Frequency Diverse Array (FDA)/Range estimation/Parameter estimation/New radar scheme分类
信息技术与安全科学引用本文复制引用
巩朋成,刘刚,黄禾,王文钦..频控阵MIMO雷达中基于稀疏迭代的多维信息联合估计方法[J].雷达学报,2018,7(2):194-201,8.基金项目
国家自然科学基金(61601178),中国博士后科学基金(2016M600729),博士科研启动金(BSQD14032)The National Natural Science Foundation of China(61601178),China Postdoctoral Science Foundation(2016M600729),The Doctoral Starting up Foundation(BSQD14032) （61601178）
