多输入多输出(Multiple-input multiple-output,MIMO)雷达利用多个天线发送和接收信号,具有超过传统相控阵的潜在优势。本文提出一种双基地MIMO雷达中基于传播算子的离开角(Direction of departure,DOD)和到达角(Direction of arrival,DOA)估计算法。该算法利用传播因子避免了对协方差矩阵特征值分解降低了运算的复杂度,并且在低信噪比和低快拍数的情况下,该算法仍具有良好的性能。与快速多目标定位算法相比,本文算法的角度估计性能有很大的提高。文中还推导出了离开角和到达角估计的均方误差。仿真结果证明了该算法的有效性。
Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Meanwhile,it identifies more DOAs than ESPRIT-like algorithm.The simulation results demonstrate its validity.
This paper discusses the blind carrier frequency offset （CFO） estimation for orthogonal frequency division multiplexing （OFDM） systems by utilizing trilinear decomposition and genera- lized preceding. Firstly, the generalized precoding is employed to obtain multiple covariance matrices which are requisite for the trilinear model, and then a novel CFO estimation algorithm is proposed for the OFDM system. Compared with both the joint diagonalizer and estimation of signal parameters via rotational invariant technique （ESPRIT）, the proposed algorithm enjoys a better CFO estimation performance. Furthermore, the proposed algorithm can work well without virtual carriers. Simulation results illustrate the performance of this algorithm,
提出一种双基地MIMO雷达L型阵列下多维角度联合估计的新算法.该算法利用匹配滤波器输出信号特点构造不同的代价函数,采用迭代最小二乘算法估计收发阵列流形矩阵,根据L型阵列结构的特点和最小二乘法,从估计出的矩阵中计算目标的二维DOD(direction of departure)和二维DOA(direction of arrival).该方法无需谱峰搜索,可实现参数的同时估计与配对.与ESPRIT算法相比,具有更高的估计精度,并接近于克拉美-罗睛限,且在小快拍数下也能较好地工作.仿真结果验证了该算法的有效性.
