SDROM

适合MATALAB的初学者使用。简单易懂，有实力支持 。(MATALAB suitable for the beginner to use. Easy-to-read, have the strength to support.)

经典的关于aster数据处理的文档。ASTER搭载在Terra卫星上的星载热量散发和反辐射仪，是于1999年12月18日发射升空的，由日本国际贸易和工业部制造。(Classic on the aster data processing documents. ASTER carrying the Terra satellite on-board heat distribution and anti-radiation device, was December 18, 1999 launched by the Japanese International Trade and Industry Manufacturing.)

使用MATLAB进行对信号的加窗和dtft计算(Carried out using the MATLAB signal increases in the calculation window and dtft)

脉冲雷达系统Simulink实现（Matlab6中可以用，Matlab7中没有试过）(pulsed radar system to achieve Simulink (Matlab can be used. Matlab7 not tried))

Digital images processing.

Spatially multiplexing several data streams onto the MIMO channel,the rank of the matrix H and with full rank.

用LAPLACE方法求解多维沃尔泰拉方程，此处为一个变元的方程，由于该方程同时含有微分和积分，一般求解有一定的困难。此处为MATLAB程序，注意不同的边界条件(used method for multiple preoperational Ertaila equation here as a variable element of the equation, As the same time contain differential equations and integral, the general solution is definitely difficult. MATLAB here for the procedures, attention to the different boundary conditions)

说明：  这是用matlab的m文件编写的fir滤波器程序(this is a fir Filter)

本程序是一般PD雷达的套完整的仿真程序，包括脉压，MTD，CFAR等过程。(This procedure is generally complete set of PD radar simulation program, including pulse pressure, MTD, CFAR and other processes.)

提出了一种多迸制频移键控(M娲K)信号调制分类及解调方法，选取截获接收机输出的MFSK信 号的时频脊线作为分类特征，利用无监督聚类算法求取最佳聚类数M．利用时频脊线的Ham：小波变换 估计码元宽度，并且利用对应最佳聚类数的聚类中心确定抽判门限，通过对时频脊线抽样判决，实现了 MFSK信号的解调．理论分析和对实际信号的处理结果证明了此算法的可行性．(new algorithm is proposed for elassillcation and demodulation of MFSK signals．The ridge of time— frequency representation of MFSK signals is analyzed．Modulation elassi_fieation is realized by using the unsupervised clustering algorithm to determine the optimal nulnllt2r of clusters．In order to demodulate MFSK signals，the Haar wavelet transform is used to estimate the code—width and the centers of optimal clusters are used to determine thresholds．Theoretical analysis and practical signal processing results justify the robusticity and the efficiency of the new classification and demodulation Mgorithm．)