基于快速张量分解的波束空间MIMO雷达二维DOA估计算法

Beamspace MIMO Radar Tensor Modeling and 2-D DOA Estimation

传统MIMO雷达由于采用全向发射模式导致目标增益损失严重,致使DOA估计算法性能较差。因此,本文提出基于波束空间MIMO雷达的张量模型和快速张量分解的二维DOA估计算法。波束空间MIMO雷达能够通过发射波束成形技术将发射能量集中到指定空域,弥补传统MIMO雷达的发射增益损失。通过高阶张量模型应用MIMO雷达多脉冲接收数据的多维结构,进一步改善DOA估计性能。由于所提方法能有效利用矩阵因子的范德蒙特结构,仅涉及矩阵运算无需优化处理,相对于传统的张量分解方法计算复杂度显著降低。同现有波束空间MIMO雷达DOA估计算法相比,所提算法具有更高的估计精度和更好的分辨能力。仿真验证了算法的有效性。

Multiple-input multiple-output(MIMO)radar suffers from the transmit energy loss due to its omni-directional transmit beampattern,and the DOA estimation methods mostly exploit only the signal covariance matrix in a single pulse,whose performance is poor at low signal-to-noise(SNR).To improve the DOA estimation performance,a higher-order tensor model and a fast tensor decomposition method are proposed for beamspace MIMO radar in application to twodimensional(2-D)direction of arrival(DOA)estimation.The designed tensor exploits the multi-linear structure of the received data in MIMO radar with multiple pulses.As compared to conventional tensor decomposition method,the proposed fast tensor decomposition method takes advantage of the Vandermonde factor matrix and requires only basic linear algebra.The computational complexity is reduced significantly.Simulation results show that the proposed method surpasses other DOA estimation methods with a better accuracy and a higher resolution.