length-scaleCs200

应用方便的OrbMath数学运算库,适用于多种语言()

自己写用于雷达直达波对消的m文件，通过抑制直达波提高目标回波信噪比(Write their own radar direct wave for the cancellation of the m documents, by inhibiting the direct wave enhance target echo signal to noise ratio)

数值计算实例，主要有LU分解，龙格库塔法，高斯分解法，欧拉法，曲线拟合，曲线插值(Numerical example)

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)

burgers方程求解，采用fortran编写，有详细的说明，效果非常好(burgers equations, using fortran prepared a detailed description of the effect is very good)

用于造波 对于从零开始学习UDF，建议还是先看一下UDF中文帮助，我估计大家知道的都是马世虎翻译的那本吧，感觉挺好。(fluent In order to learn UDF from scratch, it is suggested that we first look at UDF Chinese help.)

是用MATLABA编写的遗传运算发的一个小程序 挺好用的 大家(MATLABA is prepared by the genetic operator issued a small procedure very well, we try to use)

用于处理信号，对信号进行小波包分解，此处进行了三层分解计算，可以进行迭代。(Used to process the signal, the wavelet packet decomposition of the signal, where the three-tier decomposition of the calculation can be iterated.)

hybrid particle swarm optimization

通过滑动T检验时间序列的变化趋势，一般多用于气象分析(T-test time series by sliding the trend, generally used for weather analysis)