Nuclear norm minimization framework for DOA estimation in MIMO radar
Nuclear norm minimization framework for DOA estimation in MIMO radar
复制标题
MIMO 雷达 DOA 估计的核范数最小化框架
DOI：
10.1016/j.sigpro.2016.12.031
复制
发表时间：
2017-06-01
影响因子：
4.4
通讯作者：
Bi, Guoan
中科院分区：
文献类型：
--
作者：
Wang, Xianpeng;Wang, Luyun;Bi, Guoan
本文利用一种新的核范数最小化（NNM）框架，研究了多输入多输出（MIMO）雷达中非圆目标的波达方向（DOA）估计问题。该方法利用信号的非圆特性，扩展了阵列孔径加倍的数据模型。然后，在不考虑未知非圆相位影响的情况下，建立了扩展数据的块稀疏模型，并提出了一种基于核范数最小化的信号重构算法来恢复块稀疏矩阵。此外，基于降维非圆Capon（RD NC-Capon）谱设计了一个权矩阵，对核范数最小化进行重新加权，以增强解的稀疏性。最后，从重构矩阵的非零块估计DOA。该方法充分利用了阵列扩展孔径和块稀疏信息，具有上级DOA估计性能和较高的角分辨力。此外，所提出的方法具有低灵敏度的先验信息的源的数量。仿真结果验证了该方法的有效性和优越性。
In this paper, the direction of arrival (DOA) estimation for noncircular sources in multiple-input multiple output (MIMO) radar is dealt with by a novel nuclear norm minimization (NNM) framework. The proposed method exploits the noncircular property of signals to extend the data model for doubling the array aperture. Then a block sparse model of the extended data is formulated without the influence of the unknown noncircularity phase, and a novel signal reconstruction algorithm based on nuclear norm minimization is proposed to recover the block-sparse matrix. In addition, a weight matrix based on the reduced dimensional noncircular Capon (RD NC-Capon) spectrum is designed to reweight the nuclear norm minimization for enhancing the sparsity of solution. Finally, the DOA is estimated from the non-zero blocks of the reconstructed matrix. Due to exploiting the extended array aperture and block-sparse information, the proposed method provides superior DOA estimation performance and higher angular resolution. Furthermore, the proposed method has a low sensitivity to the priori information on the number of sources. Simulation results are presented to verify the effectiveness and advantages of the proposed method.