Imaging and recognition of targets with complex maneuvers bring a new challenge to conventional radar applications. In this paper, the three-dimensional (3D) high-resolution image is attained in real-time by a Multiple-Input-Multiple-Output (MIMO) radar system with single Orthogonal-Frequency-Division-Multiplexing (OFDM) pulse. First, to build the orthogonal transmit waveform set for MIMO transmission, we utilize complex orthogonal designs (CODs) for OFDM subcarrier modulation. Based on the OFDM modulation, a preprocessing method is developed for transmit waveform separation without conventional matched filtering. The result array manifold is the Kronecker product of the steering vectors of subcarrier/transmit antenna/receive antenna uniform linear arrays (ULAs). Then, the high-resolution image of target is attained by the Multidimensional Unitary Estimation of Signal Parameters via Rotational Invariant Techniques (MD-UESPRIT) algorithm. The proposed imaging procedures include the multidimensional spatial smoothing, the unitary transform via backward-forward averaging, and the joint eigenvalue decomposition (JEVD) algorithm for automatically paired coordinates estimation. Simulation tests compare the reconstruction results with the conventional methods and analyze the estimation precision relative to signal-to-noise ratio (SNR), system parameters, and errors.

中文翻译：

---

通过OFDM调制和单一ESPRIT的三维高分辨率MIMO雷达成像

复杂机动的目标成像和识别给常规雷达应用带来了新的挑战。在本文中，通过具有单个正交频分多路复用（OFDM）脉冲的多输入多输出（MIMO）雷达系统实时获得三维（3D）高分辨率图像。首先，为了建立用于MIMO传输的正交发射波形集，我们利用OFDM子载波调制的复杂正交设计（COD）。基于OFDM调制，开发了一种无需传统匹配滤波即可分离发射波形的预处理方法。结果阵列流形是副载波/发射天线/接收天线均匀线性阵列（ULA）的导向向量的Kronecker积。然后，通过旋转不变技术（MD-UESPRIT）算法通过信号参数的多维Unit估计获得目标的高分辨率图像。拟议的成像程序包括多维空间平滑，通过后向平均的aver变换和用于自动配对坐标估计的联合特征值分解（JEVD）算法。仿真测试将重建结果与常规方法进行比较，并分析相对于信噪比（SNR），系统参数和误差的估计精度。以及用于自动配对坐标估计的联合特征值分解（JEVD）算法。仿真测试将重建结果与常规方法进行比较，并分析相对于信噪比（SNR），系统参数和误差的估计精度。以及用于自动配对坐标估计的联合特征值分解（JEVD）算法。仿真测试将重建结果与常规方法进行比较，并分析相对于信噪比（SNR），系统参数和误差的估计精度。