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研究双基地多输入多输出(Multiple-input Multiple-output,MIMO)雷达中的角度和多普勒频率联合估计问题,提出了一种基于四线性分解(Quadrilinear Decomposition)的离开角(Direction of Departure,DOD)、波达角(Direction ofArrival,DOA)和多普勒频率的联合估计算法。通过对接收端匹配滤波器的输出进行延迟操作,得到符合四线性模型的数据,根据四线性交替最小二乘(Quadrilinear Alternating Least Squares,QALS)进行迭代,得到方向矩阵和多普勒频率矩阵的估计,进而得到角度和频率的估计。该算法无需谱峰搜索,无需知道反射系数,可实现角度和频率的自动配对,且能用于非均匀阵,该算法的角度估计性能优于多维ESPRIT方法和三线性交替最小二乘(Trilinear Alternating LeastSquares,TALS)方法。论文分析了所提算法复杂度,并推导了克拉美-罗界(Cramer-Rao bound,CRB)。仿真结果验证了该算法的有效性。
In this paper, we study the joint estimation of angle and Doppler frequency in bistatic MIMO (Multiple Input Multiple Output) radar and propose a quadratic decomposition (Quadrallinear Decomposition) DOD), Direction of Arrival (DOA) and Doppler frequency. Through the delay operation on the output of the matched filter at the receiving end, the data conforming to the four-linear model are obtained, and the quadratic linear alternating least squares (QALS) , And then get the angle and frequency estimates. The algorithm does not need spectral peak search, and does not need to know the reflection coefficient. It can realize the automatic matching of angle and frequency, and can be used for non-uniform array. Its performance is superior to multi-dimensional ESPRIT method and Trilinear Alternating Least Squares, TALS) method. The paper analyzes the complexity of the proposed algorithm and deduces Cramer-Rao bound (CRB). Simulation results verify the effectiveness of the algorithm.