ID 原文 译文
17295 针对双基地EMVS-MIMO雷达角度参数估计问题，该文通过设计新的发射阵列和接收阵列来实现对双基地EMVS-MIMO雷达角度参数估计精度的提升。 A new transmit and receive array in bistatic ElectroMagnetic Vector Sensor Multiple-Input Multiple-Output (EMVS-MIMO) radar system is designed to improve the angle parameter estimation accuracy.
17296 相比于半波长的均匀线性发射阵列和接收阵列，所设计的新型阵列能够实现发射端和接收端阵列孔径的扩展。 Compared with the bistatic EMVS-MIMO radar equipped with half -wavelength spaced uniform linear arraysboth in the transmitter and receiver, the new designed transmit and receive array can further enhance the arrayaperture.
17297 并且，为了避免发射角和接收角的角度参数额外配对过程，该文利用平行因子算法来实现发射角和接收角的角度参数自动配对。 And, automatically paired angle parameter matching process for 2D DOD and 2D DOA can beobtained with the aid of the parallel factor trilinear alternating least square algorithm.
17298 同时，相应的发射方位角、发射俯仰角、发射极化角、发射极化相位差和接收方位角、接收俯仰角、接收极化角以及接收极化相位差也是自动配对的。 Meanwhile, the corresponding elevation angle, azimuth angle, polarization angle and polarization phase difference both for transmitter and receiver are also automatically paired.
17299 通过利用平行因子算法多次迭代之后得到的方向加载矩阵，对应于发射角和接收角的精粗估计的旋转不变关系可以从方向加载矩阵中进行相应的提取。 Then, the loading matrices corresponding to transmitand receive array can be obtained by using the parallel factor trilinear alternating least square algorithm. And,high-accuracy and low-accuracy direction sine estimation can be determined by extracting the rotationinvariance relationship from the obtained loading matrices.
17300 因此，高分辨的发射角和接收角可以通过精粗估计的结合来实现。 Thus, high resolution angle parameter estimationcan be located by combining the high-accuracy estimated results and low-accuracy estimated results.
17301 相比于当前算法，所提算法具有自动参数配对特性以及较低的计算复杂度。 Furthermore, the proposed method can provide automatically paired angle parameter matching process and lower computation complexity than state-of-the-art methods.
17302 仿真实验表明所提算法具有较高的估计精度。 Simulation results are carried out to verify theexcellent angle parameter estimation performance of the proposed method.
17303 为了实现脉冲噪声环境下不受相关法分辨极限限制的高分辨率多径到达时差(TDOA)估计，该文利用相关熵理论中的最大相关熵准则(MCC)，结合将多维优化问题转化为多个1维优化问题的期望最大化方法，提出一种相关熵期望最大化(CEM)高分辨率多径TDOA估计算法。 In order to realize the high-resolution multipath Time Difference Of Arrival (TDOA) estimation which is not limited by the resolution limit of correlation method under impulsive noise environment, a Correntropy Expectation-Maximum (CEM) high resolution multipath TDOA estimation algorithm is proposed based on theMaximum Correntropy Criterion (MCC). The multipath TDOA is estimated by transforming multi-dimensionaloptimization problems into multiple one-dimensional optimization problems.
17304 仿真实验结果表明该文所提出的算法在强脉冲噪声和低信噪比的环境下都具有很好的估计性能，并且算法中参数的选取不依赖于脉冲噪声的先验信息。 The simulation results show that the CEM algorithm has good estimation performance under strong impulsive noise and low SNR environment, and the selection of kernel size in CEM algorithm is not depend on the prior information of the impulsive noise.