双基地多输入多输出雷达收发四维角联合估计

基于收发分置双L型阵多输入多输出雷达，提出了利用阵列接收数据的互相关去噪特性，进行目标辐射源收发四维角高精度联合估计的新方法。通过对匹配滤波后的阵列接收数据进行重构和互相关操作，可有效消除空间噪声影响，提高角度测量精度。将收或者发二维角的联合估计转化为两个一维估计，且只需对低维度矩阵进行特征分解，减轻了运算负担。利用特征值求取收或者发俯仰角，利用相应的特征向量构造出的虚拟阵列响应矩阵求取与其自动配对的收或者发方位角。仿真实验表明，该算法以较低的运算复杂度，实现了对空域多目标收发四维角的准确估计，估得的收或者发二维角能够自动配对，在低信噪比和短采样数据情形下，具有优良的角度估计性能。

4-D Angle Estimation for Bistatic MIMO Radar

A new approach to high resolution estimation of four-dimensional (4-D) angle of multiple narrowband far-field signals is presented for bistatic multiple-input multiple-output (MIMO) radar with double L-shaped arrays.The spatial noise can be eliminated and the angle estimation performance is improved by constructing the matched array data and making full use of the cross-correlation matrix.The proposed method decouples the two-dimensional (2-D) direction-of-arrival (DOA) or 2-D direction-ofdeparture (DOD) estimation problem into two successive one-dimensional (1-D) estimation problems,and only requires eigenvalue decomposition of lower dinensional matrix,which can reduce the computational burden.The received or transmitted elevation angles are estimated using the eigenvalues,and the corresponding received or transmitted azimuth angles are estimated through the virtual array response matrix constructed by the corresponding eigenvectors.Numerically simulated results show that the proposed method can accurately estimate the 4-D angle of multiple spatial targets with lower computational complexity,and 2-D DOA or 2-D DOD could be paired automatically.The proposed method has better angle estimation performance in the situation of low signal-to-noise ratio and short data length.