重叠阵元时分复用MIMO雷达多目标参数估计方法研究

针对多普勒-角度耦合和速度模糊问题，该文提出一种基于重叠阵元MIMO阵列的多目标参数估计方法。该方法基于虚拟孔径原理，在传统MIMO天线阵列中引入重叠阵元，构建重叠阵元MIMO天线阵列。通过在角度快速傅里叶变换(FFT)算法中引入循环迭代的方法估计阵列位置参数，利用重叠阵元回波信号的相位差值进行频率估计。同时，引入频谱搬移方法对速度区间进行转换，实现多目标的距离和速度估计。通过蒙特卡罗仿真实验，信噪比15 dB 的条件下，解模糊正确率为100%，速度误差为0.1 m/s，角度误差为0.1°。基于城市交通场景采集的车辆数据集进行测试，测试结果表明，该方法能够实现对车辆目标的速度和角度精确估计，可满足交通雷达对车辆信息监测的实时性和准确性需求。

Research on Multi-target Parameter Estimation Method for Overlapping-element Time Division Multiplexing MIMO Radar

A multitarget parameter estimation method based on overlapping element MIMO arrays is presented for Doppler-angle coupling and velocity ambiguity. Based on the virtual aperture principle, overlapping elements are introduced into the traditional MIMO antenna array to construct the overlapping element MIMO antenna array. Array position parameters are estimated by introducing a cyclic iteration into the angular Fast Fourier Transform (FFT) algorithm, and the frequency is estimated by using the phase difference of the overlapping array element echo signals. The spectral shift method is introduced to convert the speed interval to achieve multi-objective distance and speed estimation. Under the Monte Carlo simulation with 15 dB signal-to-noise ratio, the blur resolution accuracy is 100%, the speed error is 0.1 m/s, and the angle error is 0.1 degree. Tests based on the self-collected data set of urban roads show that the method can accurately estimate the speed and angle of vehicle targets, and can meet the real-time and accuracy requirements of traffic radar for vehicle information monitoring.