chazhi

针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。(To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method)

通过采集直流输电线路正负极故障电流信息，实行正负极解耦，用行波进行故障定位( U901A u8FC1 u91C0 u96C6 u76R4 u6D1 u8F93 u7535 u7EBF u8DEF u6B63 u8D1F u6781 u6545 u969C u7535 u6D41 u4D1 u606F uFF0C u5B9E u882C u6B63 u8D1F u6781 U89E3 u806 uFF0C u7528 u884C u6)

用python写的牛顿迭代法和牛顿插值法，数值分析的实验(Newton iteration method and Newton interpolation method written in Python, numerical analysis experiment.)

用于利用最大熵法求解数据资料服从的分布类型。并应用最小二乘法求解模型以得到最优解(Using the maximum entropy method for solving the data distribution type of obedience. And apply the least squares method to obtain the optimal solution to solve the model)

偏最小二乘回归在matlap中的实现，源代码，有交叉效应(The implementation of partial least squares regression in matlap, source code, cross effect)

gm模型 gm模型 gm模型 gm模型 gm模型 GM(1,1)(gm model gm model gm model gm model gm model GM (1,1))

music高阶谱分析算法，IDW距离反比加权方法，BP神经网络用于函数拟合与模式识别。( music higher order spectral analysis algorithm, IDW inverse distance weighting method, BP neural network function fitting and pattern recognition.)

利用克拉茂克郎尼变换，求得表面等离子体相位虚数部分再不同波长或入射角度的值(estimation of the imaginary part via Krammers-Kronig relarions)

说明：  经过优化的C代码实现的Gauss-Seidel 迭代算法(Optimized C code of the Gauss-Seidel iterative algorithm)

说明：  Neville插值算法，xa为自变量数组，xy为因变量数组；x为待插值的自变量(Neville interpolation algorithm, xa array as variables, xy array as the dependent variable x for the independent variables to be interpolated)