| 摘要: |
| 多输入多输出(Multiple-Input Multiple-Output，MIMO)雷达在阵元故障时虚拟阵列输出数据矩阵会出现大量的整行数据丢失，由于阵列接收数据矩阵的不完整而导致对波达方向(Direction of Arrival，DOA)的估计性能恶化。大多数低秩矩阵填充算法要求缺失数据随机分布于不完整的矩阵中，无法适用于整行缺失数据的恢复问题。为此，提出了一种基于低秩块Hankel矩阵正则化的阵元故障MIMO雷达DOA估计方法。首先，通过奇异值分解(Singular Value Decomposition，SVD)降低虚拟阵列输出矩阵的维度，以减少计算复杂度。然后，对降维数据矩阵建立基于块Hankel矩阵正则化的低秩矩阵填充模型，在该模型中将MIMO雷达降维数据矩阵排列成块Hankel 矩阵并施加Schatten-p 范数作为正则项。最后，结合交替方向乘子法(Alternate Direction Multiplier Method，ADMM)求解该模型，获得完整的MIMO雷达降维数据矩阵。仿真结果表明，所提方法能够有效恢复降维数据矩阵中的整行数据缺失，具有较高的DOA估计精度和实时性，在阵元故障率低于50.0%时DOA估计精度优于现有方法。 |
| 关键词: MIMO雷达 阵元故障 DOA估计 块Hankel矩阵 Schatten-p范数 |
| DOI：10.20079/j.issn.1001-893x.230106003 |
|
| 基金项目:国家自然科学基金资助项目（62071238）；江苏省自然科学基金项目（BK20191399） |
|
| Block Hankel Matrix Regularization Based DOA Estimation in MIMO Radar under Array Antenna Failure |
| CHEN Jinli,QU Yantao,CHEN Xuan |
| (a.School of Electronic and Information Engineering;b.School of Physics and Optoelectronic Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China) |
| Abstract: |
| The presence of multiple-input multiple-output(MIMO) radar array antenna fault leads to the entirely missing rows in the virtual array data matrix,which may damage the integrity of the array output data so as to deteriorate the performance of direction of arrival(DOA) estimation.Most low-rank matrix completion algorithms require the missing data randomly distributed in the corrupted matrix,but cannot be applied to the problem of recovering entire-row missing data.Accordingly,a low-rank block Hankel matrix regularization based method for MIMO radar DOA estimation is proposed to alleviate the negative impact of array antenna failure. |
| Key words: MIMO radar array antenna failure DOA estimation block Hankel matrix Schatten-p norm |
